Author: "Richardus, Jan" / Topic: communicable diseases - Searchworks@Jio Institute Digital Library Search Results

25 results on '"Richardus, Jan"'

1. A sharp decrease in reported non-COVID-19 notifiable infectious diseases during the first wave of the COVID-19 epidemic in the Rotterdam region, the Netherlands: a descriptive study.

Author: van Deursen B, Hagenaars M, Meima A, van Asten L, Richardus JH, Fanoy E, and Voeten H
Subjects: Humans, Netherlands epidemiology, SARS-CoV-2, Travel, Travel-Related Illness, COVID-19 epidemiology, Communicable Diseases epidemiology
Abstract: Background: The Public Health Services in the Rotterdam region, the Netherlands, observed a substantial decrease of non-COVID-19 notifiable infectious diseases and institutional outbreaks during the first wave of the COVID-19 epidemic. We describe this change from mid-March to mid-October 2020 by comparing with the pre-COVID-19 situation., Methods: All cases of notifiable diseases and institutional outbreaks reported to the Public Health Services Rotterdam-Rijnmond between 1st January and mid-October 2020 were included. Seven-day moving averages and cumulative cases were plotted against time and compared to those of 2017-2019. Additionally, Google mobility transit data of the region were plotted, as proxy for social distancing., Results: Respiratory, gastrointestinal, and travel-related notifiable diseases were reported 65% less often during the first wave of the COVID-19 epidemic than in the same weeks in 2017-2019. Reports of institutional outbreaks were also lower after the initially imposed social distancing measures; however, the numbers rebounded when measures were partially lifted., Conclusions: Interpersonal distancing and hygiene measures imposed nationally against COVID-19 were in place between mid-March and mid-October, which most likely reduced transmission of other infectious diseases, and may thus have resulted in lower notifications of infectious diseases and outbreaks. This phenomenon opens future study options considering the effect of local outbreak control measures on a wide range of non-COVID-19 diseases. Targeted, tailored, appropriate and acceptable hygiene and distancing measures, specifically for vulnerable groups and institutions, should be devised and their effect investigated., (© 2022. The Author(s).)
Published: 2022
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2. Timeliness of notification systems for infectious diseases: A systematic literature review.

Author: Swaan C, van den Broek A, Kretzschmar M, and Richardus JH
Subjects: Humans, Time Factors, Communicable Diseases, Disease Notification methods
Abstract: Introduction: Timely notification of infectious diseases is crucial for prompt response by public health services. Adequate notification systems facilitate timely notification. A systematic literature review was performed to assess outcomes of studies on notification timeliness and to determine which aspects of notification systems are associated with timely notification., Methodology: Articles reviewing timeliness of notifications published between 2000 and 2017 were searched in Pubmed and Scopus. Using a standardized notification chain, timeliness of reporting system for each article was defined as either sufficient (≥ 80% notifications in time), partly sufficient (≥ 50-80%), or insufficient (< 50%) according to the article's predefined timeframe, a standardized timeframe for all articles, and a disease specific timeframe. Electronic notification systems were compared with conventional methods (postal mail, fax, telephone, email) and mobile phone reporting., Results: 48 articles were identified. In almost one third of the studies with a predefined timeframe (39), timeliness of notification systems was either sufficient or insufficient (11/39, 28% and 12/39, 31% resp.). Applying the standardized timeframe (45 studies) revealed similar outcomes (13/45, 29%, sufficient notification timeframe, vs 15/45, 33%, insufficient). The disease specific timeframe was not met by any study. Systems involving reporting by laboratories most often complied sufficiently with predefined or standardized timeframes. Outcomes were not related to electronic, conventional notification systems or mobile phone reporting. Electronic systems were faster in comparative studies (10/13); this hardly resulted in sufficient timeliness, neither according to predefined nor to standardized timeframes., Conclusion: A minority of notification systems meets either predefined, standardized or disease specific timeframes. Systems including laboratory reporting are associated with timely notification. Electronic systems reduce reporting delay, but implementation needs considerable effort to comply with notification timeframes. During outbreak threats, patient, doctors and laboratory testing delays need to be reduced to achieve timely detection and notification. Public health authorities should incorporate procedures for this in their preparedness plans., Competing Interests: The authors have declared that no competing interests exist.
Published: 2018
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3. Public preferences for vaccination programmes during pandemics caused by pathogens transmitted through respiratory droplets - a discrete choice experiment in four European countries, 2013.

Author: Determann D, Korfage IJ, Fagerlin A, Steyerberg EW, Bliemer MC, Voeten HA, Richardus JH, Lambooij MS, and de Bekker-Grob EW
Subjects: Adolescent, Adult, Aged, Communicable Diseases immunology, Europe epidemiology, Health Surveys, Humans, Influenza Vaccines therapeutic use, Influenza, Human prevention & control, Male, Middle Aged, Netherlands epidemiology, Poland epidemiology, Predictive Value of Tests, Spain epidemiology, Sweden epidemiology, Vaccination statistics & numerical data, Young Adult, Choice Behavior, Communicable Diseases psychology, Immunization Programs statistics & numerical data, Pandemics prevention & control, Patient Acceptance of Health Care statistics & numerical data, Vaccination psychology
Abstract: This study aims to quantify and compare preferences of citizens from different European countries for vaccination programme characteristics during pandemics, caused by pathogens which are transmitted through respiratory droplets. Internet panel members, nationally representative based on age, sex, educational level and region, of four European Union Member States (Netherlands, Poland, Spain, and Sweden, n = 2,068) completed an online discrete choice experiment. These countries, from different geographical areas of Europe, were chosen because of the availability of high-quality Internet panels and because of the cooperation between members of the project entitled Effective Communication in Outbreak Management: development of an evidence-based tool for Europe (ECOM). Data were analysed using panel latent class regression models. In the case of a severe pandemic scenario, vaccine effectiveness was the most important characteristic determining vaccination preference in all countries, followed by the body that advises on vaccination. In Sweden, the advice of family and/or friends and the advice of physicians strongly affected vaccine preferences, in contrast to Poland and Spain, where the advice of (international) health authorities was more decisive. Irrespective of pandemic scenario or vaccination programme characteristics, the predicted vaccination uptakes were lowest in Sweden, and highest in Poland. To increase vaccination uptake during future pandemics, the responsible authorities should align with other important stakeholders in the country and communicate in a coordinated manner.
Published: 2016
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4. Global, regional, and national disability-adjusted life years (DALYs) for 306 diseases and injuries and healthy life expectancy (HALE) for 188 countries, 1990-2013: quantifying the epidemiological transition.

Author: Murray CJ, Barber RM, Foreman KJ, Abbasoglu Ozgoren A, Abd-Allah F, Abera SF, Aboyans V, Abraham JP, Abubakar I, Abu-Raddad LJ, Abu-Rmeileh NM, Achoki T, Ackerman IN, Ademi Z, Adou AK, Adsuar JC, Afshin A, Agardh EE, Alam SS, Alasfoor D, Albittar MI, Alegretti MA, Alemu ZA, Alfonso-Cristancho R, Alhabib S, Ali R, Alla F, Allebeck P, Almazroa MA, Alsharif U, Alvarez E, Alvis-Guzman N, Amare AT, Ameh EA, Amini H, Ammar W, Anderson HR, Anderson BO, Antonio CA, Anwari P, Arnlöv J, Arsic Arsenijevic VS, Artaman A, Asghar RJ, Assadi R, Atkins LS, Avila MA, Awuah B, Bachman VF, Badawi A, Bahit MC, Balakrishnan K, Banerjee A, Barker-Collo SL, Barquera S, Barregard L, Barrero LH, Basu A, Basu S, Basulaiman MO, Beardsley J, Bedi N, Beghi E, Bekele T, Bell ML, Benjet C, Bennett DA, Bensenor IM, Benzian H, Bernabé E, Bertozzi-Villa A, Beyene TJ, Bhala N, Bhalla A, Bhutta ZA, Bienhoff K, Bikbov B, Biryukov S, Blore JD, Blosser CD, Blyth FM, Bohensky MA, Bolliger IW, Bora Başara B, Bornstein NM, Bose D, Boufous S, Bourne RR, Boyers LN, Brainin M, Brayne CE, Brazinova A, Breitborde NJ, Brenner H, Briggs AD, Brooks PM, Brown JC, Brugha TS, Buchbinder R, Buckle GC, Budke CM, Bulchis A, Bulloch AG, Campos-Nonato IR, Carabin H, Carapetis JR, Cárdenas R, Carpenter DO, Caso V, Castañeda-Orjuela CA, Castro RE, Catalá-López F, Cavalleri F, Çavlin A, Chadha VK, Chang JC, Charlson FJ, Chen H, Chen W, Chiang PP, Chimed-Ochir O, Chowdhury R, Christensen H, Christophi CA, Cirillo M, Coates MM, Coffeng LE, Coggeshall MS, Colistro V, Colquhoun SM, Cooke GS, Cooper C, Cooper LT, Coppola LM, Cortinovis M, Criqui MH, Crump JA, Cuevas-Nasu L, Danawi H, Dandona L, Dandona R, Dansereau E, Dargan PI, Davey G, Davis A, Davitoiu DV, Dayama A, De Leo D, Degenhardt L, Del Pozo-Cruz B, Dellavalle RP, Deribe K, Derrett S, Des Jarlais DC, Dessalegn M, Dharmaratne SD, Dherani MK, Diaz-Torné C, Dicker D, Ding EL, Dokova K, Dorsey ER, Driscoll TR, Duan L, Duber HC, Ebel BE, Edmond KM, Elshrek YM, Endres M, Ermakov SP, Erskine HE, Eshrati B, Esteghamati A, Estep K, Faraon EJ, Farzadfar F, Fay DF, Feigin VL, Felson DT, Fereshtehnejad SM, Fernandes JG, Ferrari AJ, Fitzmaurice C, Flaxman AD, Fleming TD, Foigt N, Forouzanfar MH, Fowkes FG, Paleo UF, Franklin RC, Fürst T, Gabbe B, Gaffikin L, Gankpé FG, Geleijnse JM, Gessner BD, Gething P, Gibney KB, Giroud M, Giussani G, Gomez Dantes H, Gona P, González-Medina D, Gosselin RA, Gotay CC, Goto A, Gouda HN, Graetz N, Gugnani HC, Gupta R, Gupta R, Gutiérrez RA, Haagsma J, Hafezi-Nejad N, Hagan H, Halasa YA, Hamadeh RR, Hamavid H, Hammami M, Hancock J, Hankey GJ, Hansen GM, Hao Y, Harb HL, Haro JM, Havmoeller R, Hay SI, Hay RJ, Heredia-Pi IB, Heuton KR, Heydarpour P, Higashi H, Hijar M, Hoek HW, Hoffman HJ, Hosgood HD, Hossain M, Hotez PJ, Hoy DG, Hsairi M, Hu G, Huang C, Huang JJ, Husseini A, Huynh C, Iannarone ML, Iburg KM, Innos K, Inoue M, Islami F, Jacobsen KH, Jarvis DL, Jassal SK, Jee SH, Jeemon P, Jensen PN, Jha V, Jiang G, Jiang Y, Jonas JB, Juel K, Kan H, Karch A, Karema CK, Karimkhani C, Karthikeyan G, Kassebaum NJ, Kaul A, Kawakami N, Kazanjan K, Kemp AH, Kengne AP, Keren A, Khader YS, Khalifa SE, Khan EA, Khan G, Khang YH, Kieling C, Kim D, Kim S, Kim Y, Kinfu Y, Kinge JM, Kivipelto M, Knibbs LD, Knudsen AK, Kokubo Y, Kosen S, Krishnaswami S, Kuate Defo B, Kucuk Bicer B, Kuipers EJ, Kulkarni C, Kulkarni VS, Kumar GA, Kyu HH, Lai T, Lalloo R, Lallukka T, Lam H, Lan Q, Lansingh VC, Larsson A, Lawrynowicz AE, Leasher JL, Leigh J, Leung R, Levitz CE, Li B, Li Y, Li Y, Lim SS, Lind M, Lipshultz SE, Liu S, Liu Y, Lloyd BK, Lofgren KT, Logroscino G, Looker KJ, Lortet-Tieulent J, Lotufo PA, Lozano R, Lucas RM, Lunevicius R, Lyons RA, Ma S, Macintyre MF, Mackay MT, Majdan M, Malekzadeh R, Marcenes W, Margolis DJ, Margono C, Marzan MB, Masci JR, Mashal MT, Matzopoulos R, Mayosi BM, Mazorodze TT, Mcgill NW, Mcgrath JJ, Mckee M, Mclain A, Meaney PA, Medina C, Mehndiratta MM, Mekonnen W, Melaku YA, Meltzer M, Memish ZA, Mensah GA, Meretoja A, Mhimbira FA, Micha R, Miller TR, Mills EJ, Mitchell PB, Mock CN, Mohamed Ibrahim N, Mohammad KA, Mokdad AH, Mola GL, Monasta L, Montañez Hernandez JC, Montico M, Montine TJ, Mooney MD, Moore AR, Moradi-Lakeh M, Moran AE, Mori R, Moschandreas J, Moturi WN, Moyer ML, Mozaffarian D, Msemburi WT, Mueller UO, Mukaigawara M, Mullany EC, Murdoch ME, Murray J, Murthy KS, Naghavi M, Naheed A, Naidoo KS, Naldi L, Nand D, Nangia V, Narayan KM, Nejjari C, Neupane SP, Newton CR, Ng M, Ngalesoni FN, Nguyen G, Nisar MI, Nolte S, Norheim OF, Norman RE, Norrving B, Nyakarahuka L, Oh IH, Ohkubo T, Ohno SL, Olusanya BO, Opio JN, Ortblad K, Ortiz A, Pain AW, Pandian JD, Panelo CI, Papachristou C, Park EK, Park JH, Patten SB, Patton GC, Paul VK, Pavlin BI, Pearce N, Pereira DM, Perez-Padilla R, Perez-Ruiz F, Perico N, Pervaiz A, Pesudovs K, Peterson CB, Petzold M, Phillips MR, Phillips BK, Phillips DE, Piel FB, Plass D, Poenaru D, Polinder S, Pope D, Popova S, Poulton RG, Pourmalek F, Prabhakaran D, Prasad NM, Pullan RL, Qato DM, Quistberg DA, Rafay A, Rahimi K, Rahman SU, Raju M, Rana SM, Razavi H, Reddy KS, Refaat A, Remuzzi G, Resnikoff S, Ribeiro AL, Richardson L, Richardus JH, Roberts DA, Rojas-Rueda D, Ronfani L, Roth GA, Rothenbacher D, Rothstein DH, Rowley JT, Roy N, Ruhago GM, Saeedi MY, Saha S, Sahraian MA, Sampson UK, Sanabria JR, Sandar L, Santos IS, Satpathy M, Sawhney M, Scarborough P, Schneider IJ, Schöttker B, Schumacher AE, Schwebel DC, Scott JG, Seedat S, Sepanlou SG, Serina PT, Servan-Mori EE, Shackelford KA, Shaheen A, Shahraz S, Shamah Levy T, Shangguan S, She J, Sheikhbahaei S, Shi P, Shibuya K, Shinohara Y, Shiri R, Shishani K, Shiue I, Shrime MG, Sigfusdottir ID, Silberberg DH, Simard EP, Sindi S, Singh A, Singh JA, Singh L, Skirbekk V, Slepak EL, Sliwa K, Soneji S, Søreide K, Soshnikov S, Sposato LA, Sreeramareddy CT, Stanaway JD, Stathopoulou V, Stein DJ, Stein MB, Steiner C, Steiner TJ, Stevens A, Stewart A, Stovner LJ, Stroumpoulis K, Sunguya BF, Swaminathan S, Swaroop M, Sykes BL, Tabb KM, Takahashi K, Tandon N, Tanne D, Tanner M, Tavakkoli M, Taylor HR, Te Ao BJ, Tediosi F, Temesgen AM, Templin T, Ten Have M, Tenkorang EY, Terkawi AS, Thomson B, Thorne-Lyman AL, Thrift AG, Thurston GD, Tillmann T, Tonelli M, Topouzis F, Toyoshima H, Traebert J, Tran BX, Trillini M, Truelsen T, Tsilimbaris M, Tuzcu EM, Uchendu US, Ukwaja KN, Undurraga EA, Uzun SB, Van Brakel WH, Van De Vijver S, van Gool CH, Van Os J, Vasankari TJ, Venketasubramanian N, Violante FS, Vlassov VV, Vollset SE, Wagner GR, Wagner J, Waller SG, Wan X, Wang H, Wang J, Wang L, Warouw TS, Weichenthal S, Weiderpass E, Weintraub RG, Wenzhi W, Werdecker A, Westerman R, Whiteford HA, Wilkinson JD, Williams TN, Wolfe CD, Wolock TM, Woolf AD, Wulf S, Wurtz B, Xu G, Yan LL, Yano Y, Ye P, Yentür GK, Yip P, Yonemoto N, Yoon SJ, Younis MZ, Yu C, Zaki ME, Zhao Y, Zheng Y, Zonies D, Zou X, Salomon JA, Lopez AD, and Vos T
Subjects: Aged, Female, Humans, Male, Middle Aged, Mortality, Premature, Quality-Adjusted Life Years, Socioeconomic Factors, Chronic Disease epidemiology, Communicable Diseases epidemiology, Global Health statistics & numerical data, Health Transition, Life Expectancy, Wounds and Injuries epidemiology
Abstract: Background: The Global Burden of Disease Study 2013 (GBD 2013) aims to bring together all available epidemiological data using a coherent measurement framework, standardised estimation methods, and transparent data sources to enable comparisons of health loss over time and across causes, age-sex groups, and countries. The GBD can be used to generate summary measures such as disability-adjusted life-years (DALYs) and healthy life expectancy (HALE) that make possible comparative assessments of broad epidemiological patterns across countries and time. These summary measures can also be used to quantify the component of variation in epidemiology that is related to sociodemographic development., Methods: We used the published GBD 2013 data for age-specific mortality, years of life lost due to premature mortality (YLLs), and years lived with disability (YLDs) to calculate DALYs and HALE for 1990, 1995, 2000, 2005, 2010, and 2013 for 188 countries. We calculated HALE using the Sullivan method; 95% uncertainty intervals (UIs) represent uncertainty in age-specific death rates and YLDs per person for each country, age, sex, and year. We estimated DALYs for 306 causes for each country as the sum of YLLs and YLDs; 95% UIs represent uncertainty in YLL and YLD rates. We quantified patterns of the epidemiological transition with a composite indicator of sociodemographic status, which we constructed from income per person, average years of schooling after age 15 years, and the total fertility rate and mean age of the population. We applied hierarchical regression to DALY rates by cause across countries to decompose variance related to the sociodemographic status variable, country, and time., Findings: Worldwide, from 1990 to 2013, life expectancy at birth rose by 6·2 years (95% UI 5·6-6·6), from 65·3 years (65·0-65·6) in 1990 to 71·5 years (71·0-71·9) in 2013, HALE at birth rose by 5·4 years (4·9-5·8), from 56·9 years (54·5-59·1) to 62·3 years (59·7-64·8), total DALYs fell by 3·6% (0·3-7·4), and age-standardised DALY rates per 100 000 people fell by 26·7% (24·6-29·1). For communicable, maternal, neonatal, and nutritional disorders, global DALY numbers, crude rates, and age-standardised rates have all declined between 1990 and 2013, whereas for non-communicable diseases, global DALYs have been increasing, DALY rates have remained nearly constant, and age-standardised DALY rates declined during the same period. From 2005 to 2013, the number of DALYs increased for most specific non-communicable diseases, including cardiovascular diseases and neoplasms, in addition to dengue, food-borne trematodes, and leishmaniasis; DALYs decreased for nearly all other causes. By 2013, the five leading causes of DALYs were ischaemic heart disease, lower respiratory infections, cerebrovascular disease, low back and neck pain, and road injuries. Sociodemographic status explained more than 50% of the variance between countries and over time for diarrhoea, lower respiratory infections, and other common infectious diseases; maternal disorders; neonatal disorders; nutritional deficiencies; other communicable, maternal, neonatal, and nutritional diseases; musculoskeletal disorders; and other non-communicable diseases. However, sociodemographic status explained less than 10% of the variance in DALY rates for cardiovascular diseases; chronic respiratory diseases; cirrhosis; diabetes, urogenital, blood, and endocrine diseases; unintentional injuries; and self-harm and interpersonal violence. Predictably, increased sociodemographic status was associated with a shift in burden from YLLs to YLDs, driven by declines in YLLs and increases in YLDs from musculoskeletal disorders, neurological disorders, and mental and substance use disorders. In most country-specific estimates, the increase in life expectancy was greater than that in HALE. Leading causes of DALYs are highly variable across countries., Interpretation: Global health is improving. Population growth and ageing have driven up numbers of DALYs, but crude rates have remained relatively constant, showing that progress in health does not mean fewer demands on health systems. The notion of an epidemiological transition--in which increasing sociodemographic status brings structured change in disease burden--is useful, but there is tremendous variation in burden of disease that is not associated with sociodemographic status. This further underscores the need for country-specific assessments of DALYs and HALE to appropriately inform health policy decisions and attendant actions., Funding: Bill & Melinda Gates Foundation., (Copyright © 2015 Elsevier Ltd. All rights reserved.)
Published: 2015
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5. Acceptance of vaccinations in pandemic outbreaks: a discrete choice experiment.

Author: Determann D, Korfage IJ, Lambooij MS, Bliemer M, Richardus JH, Steyerberg EW, and de Bekker-Grob EW
Subjects: Adolescent, Adult, Aged, Communicable Diseases economics, Communicable Diseases immunology, Disease Susceptibility, Female, Health Expenditures, Humans, Immunization Programs statistics & numerical data, Male, Middle Aged, Netherlands, Severity of Illness Index, Surveys and Questionnaires, Choice Behavior, Communicable Diseases psychology, Models, Statistical, Pandemics prevention & control, Vaccination
Abstract: Background: Preventive measures are essential to limit the spread of new viruses; their uptake is key to their success. However, the vaccination uptake in pandemic outbreaks is often low. We aim to elicit how disease and vaccination characteristics determine preferences of the general public for new pandemic vaccinations., Methods: In an internet-based discrete choice experiment (DCE) a representative sample of 536 participants (49% participation rate) from the Dutch population was asked for their preference for vaccination programs in hypothetical communicable disease outbreaks. We used scenarios based on two disease characteristics (susceptibility to and severity of the disease) and five vaccination program characteristics (effectiveness, safety, advice regarding vaccination, media attention, and out-of-pocket costs). The DCE design was based on a literature review, expert interviews and focus group discussions. A panel latent class logit model was used to estimate which trade-offs individuals were willing to make., Results: All above mentioned characteristics proved to influence respondents' preferences for vaccination. Preference heterogeneity was substantial. Females who stated that they were never in favor of vaccination made different trade-offs than males who stated that they were (possibly) willing to get vaccinated. As expected, respondents preferred and were willing to pay more for more effective vaccines, especially if the outbreak was more serious (€6-€39 for a 10% more effective vaccine). Changes in effectiveness, out-of-pocket costs and in the body that advises the vaccine all substantially influenced the predicted uptake., Conclusions: We conclude that various disease and vaccination program characteristics influence respondents' preferences for pandemic vaccination programs. Agencies responsible for preventive measures during pandemics can use the knowledge that out-of-pocket costs and the way advice is given affect vaccination uptake to improve their plans for future pandemic outbreaks. The preference heterogeneity shows that information regarding vaccination needs to be targeted differently depending on gender and willingness to get vaccinated.
Published: 2014
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6. A qualitative exploration of social contact patterns relevant to airborne infectious diseases in northwest Bangladesh.

Author: Feenstra SG, Nahar Q, Pahan D, Oskam L, and Richardus JH
Subjects: Adolescent, Adult, Age Distribution, Aged, Bangladesh epidemiology, Educational Status, Female, Focus Groups, Hinduism, Humans, Islam, Leprosy epidemiology, Leprosy transmission, Male, Middle Aged, Rural Population statistics & numerical data, Sex Distribution, Tuberculosis epidemiology, Tuberculosis transmission, Urban Population statistics & numerical data, Young Adult, Communicable Diseases epidemiology, Communicable Diseases transmission, Interpersonal Relations, Social Behavior
Abstract: In South Asia, the burden of infectious diseases is high. Socioeconomically and culturally-defined social interaction patterns are considered to be an important determinant in the spread of diseases that are transmitted through person-to-person contact. Understanding of the contact patterns in this region can be helpful to develop more effective control measures. Focus group discussions were used in exploring social contact patterns in northwest Bangladesh. The patterns were assessed for perceived relevance to the spread of airborne infectious diseases, with special focus on diseases, like leprosy and tuberculosis, in which the role of social determinants is well-recognized. Highly-relevant social contact patterns inside the home and the neighbourhood, across age and sex groups, were reported in all group discussions. Outside the home, women and girls reported relevant contacts limited to the close neighbourhood while men mentioned high relevant contacts beyond. This implies that, in theory, infectious diseases can easily be transmitted across age and sex groups in and around the home. Adult men might play a role in the transmission of airborne infectious diseases from outside this confined area since only this group reported highly-relevant social contacts beyond the home. This concept needs further exploration but control programmes in the South Asian region could benefit from considering differences in social contact patterns by gender for risk assessments and planning of preventive interventions.
Published: 2013
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7. Establishing a standard method for analysing case detection delay in leprosy using a Bayesian modelling approach.

Author: Hambridge, Thomas, Coffeng, Luc E., de Vlas, Sake J., and Richardus, Jan Hendrik
Subjects: HANSEN'S disease, DISTRIBUTION (Probability theory), MYCOBACTERIUM leprae, LOGNORMAL distribution, COMMUNICABLE diseases, PEOPLE with disabilities
Abstract: Background: Leprosy is an infectious disease caused by Mycobacterium leprae and remains a source of preventable disability if left undetected. Case detection delay is an important epidemiological indicator for progress in interrupting transmission and preventing disability in a community. However, no standard method exists to effectively analyse and interpret this type of data. In this study, we aim to evaluate the characteristics of leprosy case detection delay data and select an appropriate model for the variability of detection delays based on the best fitting distribution type. Methods: Two sets of leprosy case detection delay data were evaluated: a cohort of 181 patients from the post exposure prophylaxis for leprosy (PEP4LEP) study in high endemic districts of Ethiopia, Mozambique, and Tanzania; and self-reported delays from 87 individuals in 8 low endemic countries collected as part of a systematic literature review. Bayesian models were fit to each dataset to assess which probability distribution (log-normal, gamma or Weibull) best describes variation in observed case detection delays using leave-one-out cross-validation, and to estimate the effects of individual factors. Results: For both datasets, detection delays were best described with a log-normal distribution combined with covariates age, sex and leprosy subtype [expected log predictive density (ELPD) for the joint model: −1123.9]. Patients with multibacillary (MB) leprosy experienced longer delays compared to paucibacillary (PB) leprosy, with a relative difference of 1.57 [95% Bayesian credible interval (BCI): 1.14–2.15]. Those in the PEP4LEP cohort had 1.51 (95% BCI: 1.08–2.13) times longer case detection delay compared to the self-reported patient delays in the systematic review. Conclusions: The log-normal model presented here could be used to compare leprosy case detection delay datasets, including PEP4LEP where the primary outcome measure is reduction in case detection delay. We recommend the application of this modelling approach to test different probability distributions and covariate effects in studies with similar outcomes in the field of leprosy and other skin-NTDs. [ABSTRACT FROM AUTHOR]
Published: 2023
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8. Identifying clusters of leprosy patients in India: A comparison of methods.

Author: Taal, Anneke T., Garg, Akshat, Lisam, Suchitra, Agarwal, Ashok, Barreto, Josafá G., van Brakel, Wim H., Richardus, Jan Hendrik, and Blok, David J.
Subjects: HANSEN'S disease, GEOGRAPHIC information systems, MYCOBACTERIUM leprae, NOISE-induced deafness, GEOGRAPHIC boundaries, COMMUNICABLE diseases
Abstract: Background: Preventive interventions with post-exposure prophylaxis (PEP) are needed in leprosy high-endemic areas to interrupt the transmission of Mycobacterium leprae. Program managers intend to use Geographic Information Systems (GIS) to target preventive interventions considering efficient use of public health resources. Statistical GIS analyses are commonly used to identify clusters of disease without accounting for the local context. Therefore, we propose a contextualized spatial approach that includes expert consultation to identify clusters and compare it with a standard statistical approach. Methodology/Principal findings: We included all leprosy patients registered from 2014 to 2020 at the Health Centers in Fatehpur and Chandauli districts, Uttar Pradesh State, India (n = 3,855). Our contextualized spatial approach included expert consultation determining criteria and definition for the identification of clusters using Density Based Spatial Clustering Algorithm with Noise, followed by creating cluster maps considering natural boundaries and the local context. We compared this approach with the commonly used Anselin Local Moran's I statistic to identify high-risk villages. In the contextualized approach, 374 clusters were identified in Chandauli and 512 in Fatehpur. In total, 75% and 57% of all cases were captured by the identified clusters in Chandauli and Fatehpur, respectively. If 100 individuals per case were targeted for PEP, 33% and 11% of the total cluster population would receive PEP, respectively. In the statistical approach, more clusters in Chandauli and fewer clusters in Fatehpur (508 and 193) and lower proportions of cases in clusters (66% and 43%) were identified, and lower proportions of population targeted for PEP was calculated compared to the contextualized approach (11% and 11%). Conclusion: A contextualized spatial approach could identify clusters in high-endemic districts more precisely than a standard statistical approach. Therefore, it can be a useful alternative to detect preventive intervention targets in high-endemic areas. Author summary: Leprosy is chronic infectious disease characterized by skin and peripheral nerve lesions. Despite the efforts to eliminate leprosy, around 210,000 new cases are still found annually of which 60% is reported by India alone. To reduce the incidence significantly, new active case finding approaches in combination with preventive treatment to at-risk populations are needed in high-endemic areas in India. Geospatial methods can support program managers and policy makers to identify clusters of leprosy patients and target at-risk populations for preventive interventions. However, often standard spatial methods do not account sufficiently for the local context (i.e., local barriers and social determinants). In this study, we describe a contextualized spatial approach that includes expert consultation to identify context specific clusters and compared it with a standard approach. Overall, our results show that the contextualized approach is able to identify more clusters precisely and covers a larger proportion of the population in clusters that would need to be targeted for preventive interventions. For program managers and policy makers, the contextualized approach can be useful to target at-risk populations in high-endemic areas while ensuring efficient use of public health resources. Further research is needed to test the scalability in different endemic settings and to apply to other Neglected Tropical Diseases. [ABSTRACT FROM AUTHOR]
Published: 2022
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9. Measuring endemicity and burden of leprosy across countries and regions: A systematic review and Delphi survey.

Author: Ogunsumi, Dorcas O., Lal, Vivek, Puchner, Karl Philipp, van Brakel, Wim, Schwienhorst-Stich, Eva-Maria, Kasang, Christa, Chukwu, Joseph, Kreibich, Saskia, Parisi, Sandra, Richardus, Jan Hendrik, and Blok, David J.
Subjects: HANSEN'S disease, MYCOBACTERIUM leprae, DELPHI method, COMMUNICABLE diseases, DISABILITIES
Abstract: Background: Leprosy is a chronic infectious disease caused by Mycobacterium leprae, the annual new case detection in 2019 was 202,189 globally. Measuring endemicity levels and burden in leprosy lacks a uniform approach. As a result, the assessment of leprosy endemicity or burden are not comparable over time and across countries and regions. This can make program planning and evaluation difficult. This study aims to identify relevant metrics and methods for measuring and classifying leprosy endemicity and burden at (sub)national level. Methods: We used a mixed-method approach combining findings from a systematic literature review and a Delphi survey. The literature search was conducted in seven databases, searching for endemicity, burden and leprosy. We reviewed the available evidence on the usage of indicators, classification levels, and scoring methods to measure and classify endemicity and burden. A two round Delphi survey was conducted to ask experts to rank and weigh indicators, classification levels, and scoring methods. Results: The literature review showed variation of indicators, levels, and cut-off values to measure leprosy endemicity and/or burden. The most used indicators for endemicity include new case detection rate (NCDR), new cases among children and new cases with grade 2 disability. For burden these include NCDR, MB cases, and prevalence. The classification levels 'high' and 'low' were most important. It was considered most relevant to use separate scoring methods for endemicity and burden. The scores would be derived by use of multiple indicators. Conclusion: There is great variation in the existing method for measuring endemicity and burden across countries and regions. Our findings contribute to establishing a standardized uniform approach to measure and classify leprosy endemicity and burden at (sub)national level, which would allow effective communication and planning of intervention strategies. Author summary: Leprosy is a chronic infectious disease caused by Mycobacterium leprae. If left untreated, it could lead to deformity and resultant disabilities. The number of new cases has remained stagnant for the past decade. Additional interventions are required tailored to the level of endemicity and burden of an area. Currently, measuring and classifying endemicity and burden in leprosy lacks a standardized uniform approach, making program planning and evaluation difficult. We did a systematic literature search and Delphi survey, a method to elicit (group) opinion from a panel of experts, to take an inventory of indicators, classification levels and cut-offs that were used to measure and classify endemicity and burden of leprosy. This study highlights the variation in usage of indicators, levels, and cut-off values to determine the endemicity and burden of leprosy across regions and countries. There was agreement that endemicity and burden should be measured separately using multiple indicators, and that the classification levels 'high' and 'low' were most important. Our findings contribute to establishing a standardized uniform approach to measure and classify leprosy endemicity and burden at (sub)national level, which would allow effective communication and planning of intervention strategies. [ABSTRACT FROM AUTHOR]
Published: 2021
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10. Number of people requiring post-exposure prophylaxis to end leprosy: A modeling study.

Author: Taal, Anneke T., Blok, David J., van Brakel, Wim H., de Vlas, Sake J., and Richardus, Jan Hendrik
Subjects: HANSEN'S disease, CONTACT tracing, COMMUNICABLE diseases, PERIPHERAL nervous system
Abstract: Background: Worldwide, around 210,000 new cases of leprosy are detected annually. To end leprosy, i.e. zero new leprosy cases, preventive interventions such as contact tracing and post-exposure prophylaxis (PEP) are required. This study aims to estimate the number of people requiring PEP to reduce leprosy new case detection (NCD) at national and global level by 50% and 90%. Methodology/Principal findings: The individual-based model SIMCOLEP was fitted to seven leprosy settings defined by NCD and MB proportion. Using data of all 110 countries with known leprosy patients in 2016, we assigned each country to one of these settings. We predicted the impact of administering PEP to about 25 contacts of leprosy patients on the annual NCD for 25 years and estimated the number of contacts requiring PEP per country for each year. The NCD trends show an increase in NCD in the first year (i.e. backlog cases) followed by a significant decrease thereafter. A reduction of 50% and 90% of new cases would be achieved in most countries in 5 and 22 years if 20.6 and 40.2 million people are treated with PEP over that period, respectively. For India, Brazil, and Indonesia together, a total of 32.9 million people requiring PEP to achieve a 90% reduction in 22 years. Conclusion/Significance: The leprosy problem is far greater than the 210,000 new cases reported annually. Our model estimates of the number of people requiring PEP to achieve significant reduction of new leprosy cases can be used by policymakers and program managers to develop long-term strategies to end leprosy. Author summary: Leprosy is a chronic infectious disease affecting the skin and peripheral nerves. Despite efforts to end leprosy, the number of new leprosy cases remains stable at around 210,000. To interrupt transmission and reduce this number significantly, new strategies such as the provision of (prophylactic) treatment need to be implemented. This should be done by targeting those most at risk of developing leprosy, the contacts of new leprosy patients. Mathematical modeling can be applied to predict the impact of preventive treatment with post-exposure prophylaxis (PEP) on the incidence and the number of contacts requiring PEP at global and national level. In this study, the cumulative number of individuals requiring PEP was estimated at 40.2 million globally to reduce the incidence by 90% in 22 years. This number provides a more realistic reflection of the size of the leprosy problem worldwide. The estimates at national level are highly relevant to all countries where leprosy has been reported as it can support the policymakers and health program makers to design their elimination strategies. It also provides insight into the investment that is required to end leprosy globally and nationally. [ABSTRACT FROM AUTHOR]
Published: 2021
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11. Minimum requirements and optimal testing strategies of a diagnostic test for leprosy as a tool towards zero transmission: A modeling study.

Author: Blok, David J., de Vlas, Sake J., Geluk, Annemieke, and Richardus, Jan Hendrik
Subjects: HANSEN'S disease, COMMUNICABLE diseases, ACTINOBACTERIA, IMMUNOLOGY, MYCOBACTERIUM
Abstract: Background: The availability of a diagnostic test to detect subclinical leprosy cases is crucial to interrupt the transmission of M. leprae. In this study we assessed the minimum sensitivity level of such a (hypothetical) diagnostic test and the optimal testing strategy in order to effectively reduce the new case detection rate (NCDR) of leprosy. Methods and findings: We used the individual-based model SIMCOLEP, and based it on previous quantification using COLEP data, a cohort study of leprosy cases in Bangladesh. The baseline consisted of treatment with Multidrug therapy of clinically diagnosed leprosy cases, passive case detection and household contact tracing. We examined the use of a leprosy diagnostic test for subclinical leprosy in four strategies: testing in 1) household contacts, 2) household contacts with a 3-year follow-up, 3) a population survey with coverage 50%, and 4) a population survey (100%). For each strategy, we varied the test sensitivity between 50% and 100%. All analyses were conducted for a high, medium, and low (i.e. 25, 5 and 1 per 100,000) endemic setting over a period of 50 years. In all strategies, the use of a diagnostic test further reduces the NCDR of leprosy compared to the no test strategy. A substantial reduction could already be achieved at a test sensitivity as low as 50%. In a high endemic setting, a NCDR of 10 per 100,000 could be reached within 8–10 years in household contact testing, and 2–6 years in a population testing. Testing in a population survey could also yield the highest number of prevented new cases, but requires a large number needed to test and treat. In contrast, household contact testing has a smaller impact on the NCDR but requires a substantially lower number needed to test and treat. Conclusions: A diagnostic test for subclinical leprosy with a sensitivity of at least 50% could substantially reduce M. leprae transmission. To effectively reduce NCDR in the short run, a population survey is preferred over household contact tracing. However, this is only favorable in high endemic settings. [ABSTRACT FROM AUTHOR]
Published: 2018
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12. African Programme for Onchocerciasis Control 1995–2015: Model-Estimated Health Impact and Cost.

Author: Coffeng, Luc E., Stolk, Wilma A., Zouré, Honorat G. M., Veerman, J. Lennert, Agblewonu, Koffi B., Murdoch, Michele E., Noma, Mounkaila, Fobi, Grace, Richardus, Jan Hendrik, Bundy, Donald A. P., Habbema, Dik, de Vlas, Sake J., and Amazigo, Uche V.
Subjects: ONCHOCERCIASIS, VISION disorders, PARASITIC diseases, EYE diseases, COMMUNICABLE diseases, SKIN diseases
Abstract: Background: Onchocerciasis causes a considerable disease burden in Africa, mainly through skin and eye disease. Since 1995, the African Programme for Onchocerciasis Control (APOC) has coordinated annual mass treatment with ivermectin in 16 countries. In this study, we estimate the health impact of APOC and the associated costs from a program perspective up to 2010 and provide expected trends up to 2015. Methods and Findings: With data on pre-control prevalence of infection and population coverage of mass treatment, we simulated trends in infection, blindness, visual impairment, and severe itch using the micro-simulation model ONCHOSIM, and estimated disability-adjusted life years (DALYs) lost due to onchocerciasis. We assessed financial costs for APOC, beneficiary governments, and non-governmental development organizations, excluding cost of donated drugs. We estimated that between 1995 and 2010, mass treatment with ivermectin averted 8.2 million DALYs due to onchocerciasis in APOC areas, at a nominal cost of about US$257 million. We expect that APOC will avert another 9.2 million DALYs between 2011 and 2015, at a nominal cost of US$221 million. Conclusions: Our simulations suggest that APOC has had a remarkable impact on population health in Africa between 1995 and 2010. This health impact is predicted to double during the subsequent five years of the program, through to 2015. APOC is a highly cost-effective public health program. Given the anticipated elimination of onchocerciasis from some APOC areas, we expect even more health gains and a more favorable cost-effectiveness of mass treatment with ivermectin in the near future. Author Summary: In 1995, the World Health Organization launched the African Programme for Onchocerciasis Control (APOC) with the aim to control morbidity due to the parasitic infectious disease onchocerciasis (river blindness). APOC aims to set up sustainable national control programs against onchocerciasis in 16 countries in sub-Saharan Africa, covering over 100 million people who are at risk for infection. The main control strategy is mass treatment with the drug ivermectin, which is donated by the pharmaceutical company Merck. Coordination of the mass treatment programs is made possible by financial contributions from donor and beneficiary countries. We estimated that between 1995 and 2010, APOC has had a huge impact on population health in sub-Saharan Africa, preventing 8.2 million years worth of healthy life from being lost due to disease and mortality, at a cost of about US$257 million. We predicted that this health impact will double during the subsequent five years, at a cost of about US$221 million. This makes APOC one of the most cost-efficient large-scale public health programs in the world. We may expect even greater health gains in the future, given the anticipated extension of the APOC mandate with the aim to eliminate infection where possible. [ABSTRACT FROM AUTHOR]
Published: 2013
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13. The Long Term Effect of Current and New Interventions on the New Case Detection of Leprosy: A Modeling Study.

Author: Fischer, Egil A. J., de Vlas, Sake J., Habbema, J. Dik F, and Richardus, Jan Hendrik
Subjects: HANSEN'S disease, COMMUNICABLE diseases, TUBERCULOSIS vaccines, BCG vaccines, MYCOBACTERIUM leprae
Abstract: Background: Although the number of newly detected leprosy cases has decreased globally, a quarter of a million new cases are detected annually and eradication remains far away. Current options for leprosy prevention are contact tracing and BCG vaccination of infants. Future options may include chemoprophylaxis and early diagnosis of subclinical infections. This study compared the predicted trends in leprosy case detection of future intervention strategies. Methods: Seven leprosy intervention scenarios were investigated with a microsimulation model (SIMCOLEP) to predict future leprosy trends. The baseline scenario consisted of passive case detection, multidrug therapy, contact tracing, and BCG vaccination of infants. The other six scenarios were modifications of the baseline, as follows: no contact tracing; with chemoprophylaxis; with early diagnosis of subclinical infections; replacement of the BCG vaccine with a new tuberculosis vaccine ineffective against Mycobacterium leprae ("no BCG"); no BCG with chemoprophylaxis; and no BCG with early diagnosis. Findings: Without contact tracing, the model predicted an initial drop in the new case detection rate due to a delay in detecting clinical cases among contacts. Eventually, this scenario would lead to new case detection rates higher than the baseline program. Both chemoprophylaxis and early diagnosis would prevent new cases due to a reduction of the infectious period of subclinical cases by detection and cure of these cases. Also, replacing BCG would increase the new case detection rate of leprosy, but this effect could be offset with either chemoprophylaxis or early diagnosis. Conclusions: This study showed that the leprosy incidence would be reduced substantially by good BCG vaccine coverage and the combined strategies of contact tracing, early diagnosis, and treatment of infection and/or chemoprophylaxis among household contacts. To effectively interrupt the transmission of M. leprae, it is crucial to continue developing immuno- and chemoprophylaxis strategies and an effective test for diagnosing subclinical infections. Author Summary: Leprosy is a contagious disease that will remain prevalent, despite the declining number of patients worldwide over the last century. With approximately 250,000 new cases detected annually, leprosy is far from being eradicated. Leprosy can be treated with drugs after disease detection. Some cases can be prevented with a tuberculosis vaccine (BCG) that cross-reacts with the bacterium responsible for leprosy, but this vaccine might be replaced in the future. Furthermore, preventive drugs can reduce the number of new cases among people in contact with infectious patients, but this strategy has not yet become established in common practice. Also, a new test is under development for the detection of infections before the appearance of symptoms. In this study, we used a computer model to assess the effectiveness of seven possible leprosy control activities. Our results showed that the decline in incidence of leprosy would slow down or halt with the introduction of a new tuberculosis vaccine that is ineffective against leprosy. However, this effect could be offset by the implementation of effective tests for early diagnosis or the routine administration of preventative drugs to contacts of patients. [ABSTRACT FROM AUTHOR]
Published: 2011
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14. The SARS epidemic in mainland China: bringing together all epidemiological data.

Author: Dan Feng, de Vlas, Sake J., Li-Qun Fang, Xiao-Na Han, Wen-Juan Zhao, Shen Sheng, Hong Yang, Zhong-Wei Jia, Richardus, Jan Hendrik, and Wu-Chun Cao
Subjects: SARS disease, EPIDEMICS, COMMUNICABLE diseases, PUBLIC health records
Abstract: Objective To document and verify the number of cases of severe acute respiratory syndrome (SARS) during the 2002–2003 epidemic in mainland China. Method All existing Chinese SARS data sources were integrated in one final database. This involved removing non-probable and duplicate cases, adding cases at the final stage of the outbreak, and collecting missing information. Results The resulting database contains a total of 5327 probable SARS cases, of whom 343 died, giving a case fatality ratio (CFR) of 6.4%. While the total number of cases happens to be equal to the original official reports, there are 5 cases overall which did not result in death. When compared with Hong Kong Special Administrative Region of China, China Taiwan, and Singapore, the SARS epidemic in mainland China resulted in a considerably lower CFR, involved relatively younger cases and included fewer health care workers. Conclusions To optimise future data collection during large-scale outbreaks of emerging or re-emerging infectious disease, China must further improve the infectious diseases reporting system, enhance collaboration between all levels of disease control, health departments, hospitals and institutes nationally and globally, and train specialized staff working at county centres of disease control. [ABSTRACT FROM AUTHOR]
Published: 2009
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15. The impact of public health control measures during the SARS epidemic in mainland China.

Author: de Vlas, Sake J., Dan Feng, Cooper, Ben S., Li-Qun Fang, Wu-Chun Cao, and Richardus, Jan Hendrik
Subjects: PUBLIC health, SARS disease, EPIDEMICS, COMMUNICABLE diseases
Abstract: We tracked the effective reproductive number ( R t) over time to assess the impact of important public health control measures in the five most SARS-affected geographic areas in mainland China. As soon as the Chinese authorities gained full control of all activities to combat SARS, R t decreased dramatically and consistently below one. Many control measures that seriously affected public life were implemented afterwards, i.e., when the epidemic was already dying down. [ABSTRACT FROM AUTHOR]
Published: 2009
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16. Polymorphism N248S in the Human Toll-Like Receptor 1 Gene Is Related to Leprosy and Leprosy Reactions.

Author: Schuring, Ron P., Hamann, Lutz, Faber, William R., Pahan, David, Richardus, Jan Hendrik, Schumann, Ralf R., and Oskam, Linda
Subjects: CRYSTALLOGRAPHY, ISOHORMONES, COMMUNICABLE diseases, MYCOBACTERIAL diseases, POPULATION genetics, AMPLIFIED fragment length polymorphism, GENETIC research, IMMUNITY, DISEASES
Abstract: We investigated the association between a polymorphism of a key innate immunity receptor, Toll-like receptor 1 (TLR1) N248S, and susceptibility to leprosy and its clinical presentation. TLR1 N248S has been shown elsewhere to diminish TLR1 signaling and subsequent leprosy disease. The homozygous genotype SS was more frequent (P = .012) and the heterozygous SN genotype was less frequent (P = .015) in patients with leprosy than in control subjects. Additional observed differences in allelic frequency in patients who experienced reversal reactions and/or erythema nodosum leprosum reactions indicates that altered TLR1 function, or at least a TLR1 N248S-linked trait, may affect the progression from infection to disease as well as the disease course and the risk of debilitating reactional episodes in this population. [ABSTRACT FROM AUTHOR]
Published: 2009
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17. Risk Perceptions and Behaviour: Towards Pandemic Control of Emerging Infectious Diseases.

Author: Brug, Johannes, Aro, Arja R., and Richardus, Jan Hendrik
Subjects: RISK perception, COMMUNICABLE diseases, SARS disease, EPIDEMICS
Abstract: The author reflects on the management and prevention of infectious diseases. He discusses the importance of complying with precautionary behaviours like wearing masks, hand hygiene and isolation. He provides details on the importance of risk perception in controlling infectious diseases and cites several studies on risk perception and infectious diseases. He also mentions the occurrence of severe acute respiratory syndrome (SARS) and other infectious diseases in 2003.
Published: 2009
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18. Perceived Threat, Risk Perception, and Efficacy Beliefs Related to SARS and Other (Emerging) Infectious Diseases: Results of an International Survey.

Author: de Zwart, Onno, Veldhuijzen, Irene K., Elam, Gillian, Aro, Arja R., Abraham, Thomas, Bishop, George D., Voeten, Hélène A. C. M., Richardus, Jan Hendrik, and Brug, Johannes
Subjects: RISK perception, SARS disease, RESPIRATORY diseases, COMMUNICABLE diseases, RISK communication, SURVEYS
Abstract: To study the levels of perceived threat, perceived severity, perceived vulnerability, response efficacy, and self-efficacy for severe acute respiratory syndrome (SARS) and eight other diseases in five European and three Asian countries. A computer-assisted phone survey was conducted among 3,436 respondents. The questionnaire focused on perceived threat, vulnerability, severity, response efficacy, and self-efficacy related to SARS and eight other diseases. Perceived threat of SARS in case of an outbreak in the country was higher than that of other diseases. Perceived vulnerability of SARS was at an intermediate level and perceived severity was high compared to other diseases. Perceived threat for SARS varied between countries in Europe and Asia with a higher perceived severity of SARS in Europe and a higher perceived vulnerability in Asia. Response efficacy and self-efficacy for SARS were higher in Asia compared to Europe. In multiple linear regression analyses, country was strongly associated with perceived threat. The relatively high perceived threat for SARS indicates that it is seen as a public health risk and offers a basis for communication in case of an outbreak. The strong association between perceived threat and country and different regional patterns require further research. [ABSTRACT FROM AUTHOR]
Published: 2009
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19. Physical Distance, Genetic Relationship, Age, and Leprosy Classification Are Independent Risk Factors for Leprosy in Contacts of Patients with Leprosy.

Author: Moet, F. Johannes, Pahan, David, Schuring, Ron P., Oskam, Linda, and Richardus, Jan H.
Subjects: HANSEN'S disease, COMMUNICABLE diseases, MYCOBACTERIAL diseases, DISEASE risk factors, REGRESSION analysis, BACTERIAL diseases
Abstract: Background. Close contacts of patients with leprosy have a higher risk of developing leprosy. Several risk factors have been identified, including genetic relationship and physical distance. Their independent contributions to the risk of developing leprosy, however, have never been sufficiently quantified. Methods. Logistic-regression analysis was performed on intake data from a prospective cohort study of 1037 patients newly diagnosed as having leprosy and their 21,870 contacts. Results. Higher age showed an increased risk, with a bimodal distribution. Contacts of patients with pauci-bacillary (PB) leprosy with 2-5 lesions (PB2-5) and those with multibacillary (MB) leprosy had a higher risk than did contacts of patients with single-lesion PB leprosy. The core household group had a higher risk than other contacts living under the same roof and next-door neighbors, who again had a higher risk than neighbors of neighbors. A close genetic relationship indicated an increased risk when blood-related children, parents, and siblings were pooled together. Conclusions. Age of the contact, the disease classification of the index patient, and physical and genetic distance were independently associated with the risk of a contact acquiring leprosy. Contact surveys in leprosy should be not only focused on household contacts but also extended to neighbors and consanguineous relatives, especially when the patient has PB2-5 or MB leprosy. [ABSTRACT FROM AUTHOR]
Published: 2006
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20. Black--White Differences in Infectious Disease Mortality in the United States.

Author: Richardus, Jan H. and Kunst, Anton E.
Subjects: *ETHNICITY, *GROUP identity, *BLACK people, *WHITE people, *COMMUNICABLE diseases, *MORTALITY, *LONGITUDINAL method
Abstract: Conclusions. In the United States, infectious diseases account for nearly 10% of the excess all-cause mortality rates in Blacks compared with Whites. (Am J Public Health. 2001;91:1251-1253) [ABSTRACT FROM AUTHOR]
Published: 2001
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21. Leprosy remains an important public health challenge in India.

Author: Richardus, Jan Hendrik
Subjects: *HANSEN'S disease, *COMMUNICABLE diseases, *CHILDREN with disabilities, *DISABILITIES
Abstract: The article provides a commentary on leprosy as a public health challenge in India. A total of 127,295 cases of new leprosy were registered in the country in 2011. Leprosy is identified as a leading cause of preventable disability among Indian children. The author criticizes the disability-adjusted life years (DALY) as an indicator to describe the burden of the disease and introduces an alternative indicator called the disability adjusted working life years (DAWLY).
Published: 2013

22. Chapter Two - Mathematical Modelling of Leprosy and Its Control.

Author: Blok, David J., de Vlas, Sake J., Fischer, Egil A. J., and Richardus, Jan Hendrik
Subjects: *DRUG therapy for Hansen's disease, *HANSEN'S disease treatment, *HANSEN'S disease, *MATHEMATICAL models, *COMMUNICABLE diseases, *MYCOBACTERIUM leprae, *DECISION making, *EPIDEMIOLOGY, *INFECTIOUS disease transmission
Abstract: Leprosy or Hansen's disease is an infectious disease caused by the bacterium Mycobacterium leprae. The annual number of new leprosy cases registered worldwide has remained stable over the past years at over 200,000. Early case finding and multidrug therapy have not been able interrupt transmission completely. Elimination requires innovation in control and sustained commitment. Mathematical models can be used to predict the course of leprosy incidence and the effect of intervention strategies. Two compartmental models and one individual-based model have been described in the literature. Both compartmental models investigate the course of leprosy in populations and the long-term impact of control strategies. The individual-based model focusses on transmission within households and the impact of case finding among contacts of new leprosy patients. Major improvement of these models should result from a better understanding of individual differences in exposure to infection and developing leprosy after exposure. Most relevant are contact heterogeneity, heterogeneity in susceptibility and spatial heterogeneity. Furthermore, the existing models have only been applied to a limited number of countries. Parameterization of the models for other areas, in particular those with high incidence, is essential to support current initiatives for the global elimination of leprosy. Many challenges remain in understanding and dealing with leprosy. The support of mathematical models for understanding leprosy epidemiology and supporting policy decision making remains vital. [ABSTRACT FROM AUTHOR]
Published: 2015
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23. Management of Chlamydia Cases and Their Partners: Results From a Home-Based Screening Program Organized by Municipal Publlc Health Services With Referral to Regular Health Care.

Author: Göotz, Hannelore M., Hoebe, Christian J. P. A., Van Bergen, Jan E. A. M., Irene K. Veldhuijzen, Broer, Jan, De Groot, F., Verhooren, M. J. C., Van Schaik, D. T., Coenen, A. J. J., and Richardus, Jan H.
Subjects: *CHLAMYDIA infections, *SEXUALLY transmitted diseases, *COMMUNICABLE diseases, *PUBLIC health, *CHLAMYDIA trachomatis
Abstract: Background: We evaluated the management of Chlamydia trachomatis cases and partners found in a systematic home-based chlamydia screening project in the Netherlands among 15- to 29-year-old women and men, organized by the Municipal Public Health Services (MHS). Methods: Infected participants (165/8339 = 2%) were referred to regular curative services. The treating physician provided feedback on treatment and partner notification. Results: Including the effect of a reminder, the treatment rate of all index cases was 91% (150/165); among persons with non-Dutch ethnicity, 81% (25/31). The majority of cases (82%) consulted the general practitioner for treatment as opposed to sexually transmitted disease/ MHS clinics (18%). Eighty-five percent of cases were treated within 2 weeks. The confirmed treatment rate of partners in the last 6 months was 49% (86/176); 57% (81/141) for current versus 14% (5/35) for other partners. Patient referral was advised in an additional 18% (25/141) of current partners and in 9% (3/35) of other partners (potential treatment). Conclusion: Home-based chlamydia screening and treatment through regular treatment facilities has proven to be effective in the Netherlands. The necessity of a reminder to increase treatment rate and the lower treatment rate in non-Dutch high-risk groups deserve attention. Low confirmed treatment rate of current partners carries the potential of reinfection, and patient-delivered treatment should be expanded. [ABSTRACT FROM AUTHOR]
Published: 2005
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24. The future incidence of leprosy:a scenario analysis.

Author: Meima, Abraham, Smith, W. Cairns S., Van Oortmarssen, Gerrit J., Richardus, Jan H., and Habbema, J. Dik F.
Subjects: *HANSEN'S disease, *SURGERY, *COMMUNICABLE diseases, *MYCOBACTERIAL diseases, *BCG vaccines
Abstract: Objective: To investigate the impact of the current strategy for the elimination of leprosy on its incidence and to assess the consequences of failure to sustain this strategy. Methods: Scenarios for assessing the impact of the elimination strategy were implemented in a computer program. The scenarios reflected the assumptions made regarding contagiousness, transmission and bacille Calmette-Guérin (BCG) vaccination. The trend in case detection rate for the main countries in which leprosy was endemic during 1985-1998 was fitted, and incidence up to 2020 was projected. Findings: Owing to the gradual shortening of delays in detection up to 1998, and because of the low relapse rate that occurs with multidrug treatment MDT, incidence is predicted to decrease beyond 2000 in all scenarios. The annual decline was a few per cent higher when favourable assumption were made about protection and coverage of BCG vaccination. Overall, the predicted annual decline in incidences range from 2% to 12%. Conclusion: The elimination strategy reduces transmission, but the decline may be slow. Relaxation of control after 2005 is unjustified given the uncertainty about the rate of decline and the adverse effects of longer delays in detection. A long-term strategy for leprosy control should be adopted. [ABSTRACT FROM AUTHOR]
Published: 2004

25. Global, regional, and national disability-adjusted life years (DALYs) for 306 diseases and injuries and healthy life expectancy (HALE) for 188 countries, 1990-2013

Author: Meghan D. Mooney, Ken Takahashi, Andrea Stewart, Jonathan C Brown, Shireen Sindi, Amany H Refaat, Ruben Castro, Sara Sheikhbahaei, Kyle R. Heuton, Gillian M. Hansen, Chante Karimkhani, Bryan K. Phillips, Ibrahim Abubakar, Yohannes Kinfu, Victoria F Bachman, Konstantinos Stroumpoulis, Megan Coggeshall, Lucía Cuevas-Nasu, Yichong Li, Vineet K. Chadha, Andrew G. M. Bulloch, Takayoshi Ohkubo, Don C. Des Jarlais, Giancarlo Logroscino, Francis Apolinary Mhimbira, Jefferson G Fernandes, Cheng Huang, Ejaz Ahmad Khan, Fortuné Gbètoho Gankpé, Roderick J Hay, Itamar S. Santos, Zanfina Ademi, Fiona J Charlson, Norlinah Mohamed Ibrahim, Anwar Rafay, Andrew L. Thorne-Lyman, Juanita A. Haagsma, Emmanuel A. Ameh, John J. McGrath, Massimo Cirillo, Wubegzier Mekonnen, Holly Hagan, Naohiro Yonemoto, Frida Namnyak Ngalesoni, Dietrich Plass, Matias Trillini, David Phillips, Braden Te Ao, Wanqing Chen, Yun Jin Kim, David Rojas-Rueda, Christina Papachristou, Andrew E. Moran, Richard A. Gosselin, Maziar Moradi-Lakeh, Soraya Seedat, Janet L Leasher, Belinda K Lloyd, Lorenzo Monasta, Bruno F. Sunguya, Eun-Kee Park, Eduardo A. Undurraga, Mohammad A. AlMazroa, Mohammad H. Forouzanfar, Young-Ho Khang, Vasiliki Stathopoulou, Dima M. Qato, James Scott, Ileana Heredia-Pi, Luca Ronfani, Haidong Kan, Tasara T. Mazorodze, Murugesan Raju, Saeid Shahraz, Taavi Tillmann, Wang Wenzhi, Neil Pearce, Eric Y. Tenkorang, Aliya Naheed, Ferrán Catalá-López, Sudan Prasad Neupane, Emily Dansereau, Michael McKee, Derrick A Bennett, Mazeda Hossain, Paul S. F. Yip, Grant Nguyen, Norberto Perico, Miguel Angel Alegretti, Babak Eshrati, Boris Bikbov, Palwasha Anwari, Guoqing Hu, Amelia Bertozzi-Villa, Peter A. Meaney, Farshad Farzadfar, Svetlana Popova, Tara Templin, Hmwe H Kyu, Uche S. Uchendu, Kebede Deribe, Sergey Soshnikov, Nobhojit Roy, Daniel Kim, Ilana N. Ackerman, Homie Razavi, Leslie T. Cooper, Sandra Nolte, David T. Felson, John J Huang, Yang Liu, Fiorella Cavalleri, Adrian Davis, Héctor Gómez Dantés, Klara Dokova, Yuantao Hao, Catalina Medina, Austin E Schumacher, Stan Biryukov, Jane Rowley, Arindam Basu, Jose C. Adsuar, Rosana E. Norman, Yousef Khader, Rafael Alfonso-Cristancho, Sukanta Saha, Simón Barquera, Diego Gonzalez-Medina, Philip B. Mitchell, Lars Barregard, Haidong Wang, Yongmei Li, Ami R. Moore, Marie Ng, Raghib Ali, Peter T. Serina, Lijing L Yan, Ayse Abbasoglu Ozgoren, Ricky Leung, Michelle L. Bell, Tim Driscoll, Azmeraw T. Amare, Farshad Pourmalek, Tea Lallukka, Benjamin O Anderson, Raimundas Lunevicius, Corine Karema, Robert G. Weintraub, Erin C Mullany, Anders Larsson, Glen Mola, Paulo A. Lotufo, Luke Nyakarahuka, Sayed Saidul Alam, Louisa Degenhardt, Hugh R. Taylor, E. 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Venkat, Nejjari, Chakib, Neupane, Sudan P., Newton, Charles R., Ng, Marie, Ngalesoni, Frida N., Nguyen, Grant, Nisar, Muhammad I., Nolte, Sandra, Norheim, Ole F., Norman, Rosana E., Norrving, Bo, Nyakarahuka, Luke, Oh, In-Hwan, Ohkubo, Takayoshi, Ohno, Summer L., Olusanya, Bolajoko O., Opio, John Nelson, Ortblad, Katrina, Ortiz, Alberto, Pain, Amanda W., Pandian, Jeyaraj D., Panelo, Carlo Irwin A., Papachristou, Christina, Park, Eun-Kee, Park, Jae-Hyun, Patten, Scott B., Patton, George C., Paul, Vinod K., Pavlin, Boris I., Pearce, Neil, Pereira, David M., Perez-Padilla, Rogelio, Perez-Ruiz, Fernando, Perico, Norberto, Pervaiz, Aslam, Pesudovs, Konrad, Peterson, Carrie B., Petzold, Max, Phillips, Michael R., Phillips, Bryan K., Phillips, David E., Piel, Frédéric B., Plass, Dietrich, Poenaru, Dan, Polinder, Suzanne, Pope, Daniel, Popova, Svetlana, Poulton, Richie G., Pourmalek, Farshad, Prabhakaran, Dorairaj, Prasad, Noela M., Pullan, Rachel L., Qato, Dima M., Quistberg, D Alex, Rafay, Anwar, Rahimi, Kazem, Rahman, Sajjad U., Raju, Murugesan, Rana, Saleem M., Razavi, Homie, Reddy, K Srinath, Refaat, Amany, Remuzzi, Giuseppe, Resnikoff, Serge, Ribeiro, Antonio L., Richardson, Lee, Richardus, Jan Hendrik, Roberts, D Allen, Rojas-Rueda, David, Ronfani, Luca, Roth, Gregory A., Rothenbacher, Dietrich, Rothstein, David H., Rowley, Jane T., Roy, Nobhojit, Ruhago, George M., Saeedi, Mohammad Y., Saha, Sukanta, Sahraian, Mohammad Ali, Sampson, Uchechukwu K. A., Sanabria, Juan R., Sandar, Logan, Santos, Itamar S., Satpathy, Maheswar, Sawhney, Monika, Scarborough, Peter, Schneider, Ione J., Schöttker, Ben, Schumacher, Austin E., Schwebel, David C., Scott, James G., Seedat, Soraya, Sepanlou, Sadaf G., Serina, Peter T., Servan-Mori, Edson E., Shackelford, Katya A., Shaheen, Amira, Shahraz, Saeid, Levy, Teresa Shamah, Shangguan, Siyi, She, Jun, Sheikhbahaei, Sara, Shi, Peilin, Shibuya, Kenji, Shinohara, Yukito, Shiri, Rahman, Shishani, Kawkab, Shiue, Ivy, Shrime, Mark G., Sigfusdottir, Inga D., Silberberg, Donald H., Simard, Edgar P., Sindi, Shireen, Singh, Abhishek, Singh, Jasvinder A., Singh, Lavanya, Skirbekk, Vegard, Slepak, Erica Leigh, Sliwa, Karen, Soneji, Samir, Søreide, Kjetil, Soshnikov, Sergey, Sposato, Luciano A., Sreeramareddy, Chandrashekhar T., Stanaway, Jeffrey D., Stathopoulou, Vasiliki, Stein, Dan J., Stein, Murray B., Steiner, Caitlyn, Steiner, Timothy J., Stevens, Antony, Stewart, Andrea, Stovner, Lars J., Stroumpoulis, Konstantino, Sunguya, Bruno F., Swaminathan, Soumya, Swaroop, Mamta, Sykes, Bryan L., Tabb, Karen M., Takahashi, Ken, Tandon, Nikhil, Tanne, David, Tanner, Marcel, Tavakkoli, Mohammad, Taylor, Hugh R., Te Ao, Braden J., Tediosi, Fabrizio, Temesgen, Awoke M., Templin, Tara, Ten Have, Margreet, Tenkorang, Eric Y., Terkawi, Abdullah S., Thomson, Blake, Thorne-Lyman, Andrew L., Thrift, Amanda G., Thurston, George D., Tillmann, Taavi, Tonelli, Marcello, Topouzis, Foti, Toyoshima, Hideaki, Traebert, Jefferson, Tran, Bach X., Trillini, Matia, Truelsen, Thoma, Tsilimbaris, Miltiadi, Tuzcu, Emin M., Uchendu, Uche S., Ukwaja, Kingsley N., Undurraga, Eduardo A., Uzun, Selen B., Van Brakel, Wim H., Van De Vijver, Steven, Van Gool, Coen H., Van Os, Jim, Vasankari, Tommi J., Venketasubramanian, N, Violante, Francesco S., Vlassov, Vasiliy V., Vollset, Stein Emil, Wagner, Gregory R., Wagner, Joseph, Waller, Stephen G., Wan, Xia, Wang, Haidong, Wang, Jianli, Wang, Linhong, Warouw, Tati S., Weichenthal, Scott, Weiderpass, Elisabete, Weintraub, Robert G., Wenzhi, Wang, Werdecker, Andrea, Westerman, Ronny, Whiteford, Harvey A., Wilkinson, James D., Williams, Thomas N., Wolfe, Charles D., Wolock, Timothy M., Woolf, Anthony D., Wulf, Sarah, Wurtz, Brittany, Xu, Gelin, Yan, Lijing L., Yano, Yuichiro, Ye, Pengpeng, Yentür, Gökalp K., Yip, Paul, Yonemoto, Naohiro, Yoon, Seok-Jun, Younis, Mustafa Z., Yu, Chuanhua, Zaki, Maysaa E., Zhao, Yong, Zheng, Yingfeng, Zonies, David, Zou, Xiaonong, Salomon, Joshua A., Lopez, Alan D., Vos, Theo, Medische Sociologie, MUMC+: Hersen en Zenuw Centrum (3), MUMC+: MA Psychiatrie (3), Psychiatrie & Neuropsychologie, Barber, Ryan M, Foreman, Kyle J, Abd Allah, Foad, Abera, Semaw F, Abraham, Jerry P, Abu Raddad, Laith J, Abu Rmeileh, Niveen M, Ackerman, Ilana N, Adou, Arsène K, Adsuar, José C, Agardh, Emilie E, Albittar, Mohammed I, Alegretti, Miguel A, Alemu, Zewdie A, Alfonso Cristancho, Rafael, Almazroa, Mohammad A, Alvis Guzman, Nelson, Amare, Azmeraw T, Ameh, Emmanuel A, Anderson, Benjamin O, Antonio, Carl Abelardo T, Asghar, Rana J, Atkins, Lydia S, Avila, Marco A, Bachman, Victoria F, Bahit, Maria C, Barker Collo, Suzanne L, Barrero, Lope H, Basulaiman, Mohammed O, Bell, Michelle L, Bennett, Derrick A, Bensenor, Isabela M, Bertozzi Villa, Amelia, Beyene, Tariku J, Bhutta, Zulfiqar A, Blore, Jed D, Blosser, Christopher D, Blyth, Fiona M, Bohensky, Megan A, Bolliger, Ian W, Bornstein, Natan M, Bourne, Rupert R. A, Boyers, Lindsay N, Brayne, Carol E, Breitborde, Nicholas J. K, Briggs, Adam D, Brooks, Peter M, Brown, Jonathan C, Brugha, Traolach S, Buckle, Geoffrey C, Budke, Christine M, Bulloch, Andrew G, Campos Nonato, Ismael R, Carapetis, Jonathan R, Carpenter, David O, Castañeda Orjuela, Carlos A, Castro, Ruben E, Catalá López, Ferrán, Chadha, Vineet K, Chang, Jung Chen, Charlson, Fiona J, Chiang, Peggy P, Chimed Ochir, Odgerel, Christophi, Costas A, Coates, Matthew M, Coffeng, Luc E, Coggeshall, Megan S, Colquhoun, Samantha M, Cooke, Graham S, Cooper, Leslie T, Coppola, Luis M, Criqui, Michael H, Crump, John A, Cuevas Nasu, Lucia, Dargan, Paul I, Davitoiu, Dragos V, Del Pozo Cruz, Borja, Dellavalle, Robert P, Jarlais, Don C. De, Dharmaratne, Samath D, Dherani, Mukesh K, Diaz Torné, Cesar, Ding, Eric L, Dorsey, E. 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Dean, Hotez, Peter J, Hoy, Damian G, Huang, John J, Iannarone, Marissa L, Iburg, Kim M, Jacobsen, Kathryn H, Jarvis, Deborah L, Jassal, Simerjot K, Jensen, Paul N, Jonas, Jost B, Karema, Corine K, Kassebaum, Nicholas J, Kemp, Andrew H, Kengne, Andre P, Khader, Yousef S, Khalifa, Shams Eldin A, Khan, Ejaz A, Khang, Young Ho, Kinge, Jonas M, Knibbs, Luke D, Kuipers, Ernst J, Kulkarni, Veena S, Kumar, G. Anil, Kyu, Hmwe H, Lansingh, Van C, Lawrynowicz, Alicia E. 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Venkat, Neupane, Sudan P, Newton, Charles R, Ngalesoni, Frida N, Nisar, Muhammad I, Norheim, Ole F, Norman, Rosana E, Oh, In Hwan, Ohno, Summer L, Olusanya, Bolajoko O, Pain, Amanda W, Pandian, Jeyaraj D, Panelo, Carlo Irwin A, Park, Eun Kee, Park, Jae Hyun, Patten, Scott B, Patton, George C, Paul, Vinod K, Pavlin, Boris I, Pereira, David M, Perez Padilla, Rogelio, Perez Ruiz, Fernando, Peterson, Carrie B, Phillips, Michael R, Phillips, Bryan K, Phillips, David E, Piel, Frédéric B, Poulton, Richie G, Prasad, Noela M, Pullan, Rachel L, Qato, Dima M, Quistberg, D. Alex, Rahman, Sajjad U, Rana, Saleem M, Reddy, K. Srinath, Ribeiro, Antonio L, Roberts, D. Allen, Rojas Rueda, David, Roth, Gregory A, Rothstein, David H, Rowley, Jane T, Ruhago, George M, Saeedi, Mohammad Y, Sampson, Uchechukwu K. A, Sanabria, Juan R, Santos, Itamar S, Schneider, Ione J, Schumacher, Austin E, Schwebel, David C, Scott, James G, Sepanlou, Sadaf G, Serina, Peter T, Servan Mori, Edson E, Shackelford, Katya A, Shrime, Mark G, Sigfusdottir, Inga D, Silberberg, Donald H, Simard, Edgar P, Singh, Jasvinder A, Sposato, Luciano A, Sreeramareddy, Chandrashekhar T, Stanaway, Jeffrey D, Stein, Dan J, Stein, Murray B, Steiner, Timothy J, Stovner, Lars J, Sunguya, Bruno F, Sykes, Bryan L, Tabb, Karen M, Taylor, Hugh R, Ao, Braden J. Te, Temesgen, Awoke M, Tenkorang, Eric Y, Terkawi, Abdullah S, Thorne Lyman, Andrew L, Thrift, Amanda G, Thurston, George D, Tran, Bach X, Tuzcu, Emin M, Uchendu, Uche S, Ukwaja, Kingsley N, Undurraga, Eduardo A, Uzun, Selen B, Van Brakel, Wim H, van Gool, Coen H, Vasankari, Tommi J, Violante, Francesco S, Vlassov, Vasiliy V, Wagner, Gregory R, Waller, Stephen G, Warouw, Tati S, Weintraub, Robert G, Whiteford, Harvey A, Wilkinson, James D, Williams, Thomas N, Wolfe, Charles D, Wolock, Timothy M, Woolf, Anthony D, Yan, Lijing L, Yentür, Gökalp K, Yoon, Seok Jun, Younis, Mustafa Z, Zaki, Maysaa E, Salomon, Joshua A, Lopez, Alan D, Computational Science and Engineering Department [Daresbury] ( STFC ), Science & Technologie Facilities Council, Neuroépidémiologie Tropicale ( NET ), CHU Limoges-Institut d'Epidémiologie Neurologique et de Neurologie Tropicale-Institut National de la Santé et de la Recherche Médicale ( INSERM ) -Institut Génomique, Environnement, Immunité, Santé, Thérapeutique ( GEIST ), Université de Limoges ( UNILIM ) -Université de Limoges ( UNILIM ), Service de Chirurgie Thoracique et Vasculaire - Médecine vasculaire [CHU Limoges], CHU Limoges, Weill Cornell Medical College - Qatar, Qatar Foundation - Education City, Doha, Maladies chroniques, santé perçue, et processus d'adaptation ( APEMAC ), Université Paris Descartes - Paris 5 ( UPD5 ) -Université de Lorraine ( UL ), Centre d'Investigation Clinique - Epidemiologie Clinique/essais Cliniques Nancy, Cancéropôle du Grand Est-Institut National de la Santé et de la Recherche Médicale ( INSERM ), Karolinska Institute, karolinska institute, Centro de Estudios Avanzados en Zonas Aridas ( CEAZA ), Ecole Polytechnique Fédérale de Lausanne ( EPFL ), Wisconsin Division of Public Health, Regional Genetic Service, St Mary's Hospital, Manchester, Laboratoire d'Ingénierie des Matériaux ( LIM ), Centre National de la Recherche Scientifique ( CNRS ), Computer Science Department [Bristol], University of Bristol [Bristol], Lawrence Berkeley National Laboratory [Berkeley] ( LBNL ), Samsung Research &Development Institute India - Bangalore (Groupe Samsung) ( SRI-B ), Multimedia Research Center ( MRC ), University of Alberta [Edmonton], Division of Biostatistics ( Biostat - MINNEAPOLIS ), University of Minnesota [Minneapolis], Laboratory of Neurologic Diseases, Mario Negri Institute, Milan, University of Southampton [Southampton], Imperial College London, Neurology Department, Ichilov Medical Center, Department of Public Health and Primary Care, Cambridge University, Interactions, transferts, ruptures artistiques et culturels - EA 6301 ( InTRu ), Université de Tours, Institut Jacques Monod ( IJM ), Université Paris Diderot - Paris 7 ( UPD7 ) -Centre National de la Recherche Scientifique ( CNRS ), Institute of Parasitology, STAR laboratory, Stanford University [Stanford], Unité de recherche Virologie et Immunologie Moléculaires ( VIM ), Institut National de la Recherche Agronomique ( INRA ), Tennent Institute of Ophthalmology, National University of Singapore ( NUS ), Multidisciplinary Nanotechnology Centre, Swansea University, Department of Computer Sciences [Scheffield], University of Sheffield [Sheffield], Cyprus International Institute for the Environment and Public Health, Harvard School of Public Health, Glasgow Centre for Physical Organic Chemistry, University of Glasgow, King‘s College London, Université Panthéon-Sorbonne - 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UFR Médecine ( UGA UFRM ), Université Grenoble Alpes ( UGA ), Clinical Epidemiology and Aging Research, German Cancer Research Center, Institut Cochin ( UM3 (UMR 8104 / U1016) ), Université Paris Descartes - Paris 5 ( UPD5 ) -Institut National de la Santé et de la Recherche Médicale ( INSERM ) -Centre National de la Recherche Scientifique ( CNRS ), Symantec, European Microsoft Innovation Center ( EMIC ), Microsoft Corporation [Redmond, Wash.], Laboratoire de Mécanique, Physique et Géosciences ( LMPG ), Université Le Havre Normandie ( ULH ), Normandie Université ( NU ) -Normandie Université ( NU ), Novartis institute for tropical diseases, Institut de Génétique et de Biologie Moléculaire et Cellulaire ( IGBMC ), Université de Strasbourg ( UNISTRA ) -Institut National de la Santé et de la Recherche Médicale ( INSERM ) -Centre National de la Recherche Scientifique ( CNRS ), Departments of Anatomy and Cell Biology, Wayne State University School of Medicine, Departments of Ophthalmology, Departments of Applied Physics [New Haven], Yale University [New Haven], Center for Mathematical Modeling ( CMM ), Universidad de Santiago de Chile [Santiago] ( USACH ), Laboratory for Atmospheric and Space Physics [Boulder] ( LASP ), University of Colorado Boulder [Boulder], University of Occupational and Environmental Health [Kitakyushu] ( UEOH ), Department of Computer Science and Engineering [New Delhi], Indian Institute of Technology Delhi ( IIT Delhi ), Institut de Recherche sur les Phénomènes Hors Equilibre ( IRPHE ), Aix Marseille Université ( AMU ) -Ecole Centrale de Marseille ( ECM ) -Centre National de la Recherche Scientifique ( CNRS ), GlaxoSmithKline, Imperial College London-Clinical Imaging Center, Department of Obstetrics, Gynecology and Reproductive Sciences, Yale University School of Medicine, Yale School of Medicine-Yale School of Medicine-Yale Stem Cell Center, Maclean Building, Benson Lane, Crowmarsh Gifford, Centre for Ecology and Hydrology, Nanoscience Institute ( NEST ), Dipartimento di Fisica, Università di Pisa, Aristotle University of Thessaloniki, Laboratory Of Immune Cell Biology ( LICB ), National Institutes of Health ( NIH ), Institute of Human Genetics, Bonn Universität [Bonn], Occupational Health Unit, Bologna University Hospital-Sant'Orsola-Malpighi Polyclinic, Royal Institute of Technology [Stockholm] ( KTH ), Institut für Informatik [München/Munich] ( LMU ), Ludwig-Maximilians-Universität München, NICTA [Eveleigh], National ICT Australia [Sydney] ( NICTA ), Manchester Academic Health Sciences Centre, Institut d'Histoire et de Philosophie des Sciences et des Techniques ( IHPST ), Université Panthéon-Sorbonne ( UP1 ) -Département d'Etudes Cognitives - ENS Paris ( DEC ), École normale supérieure - Paris ( ENS Paris ) -École normale supérieure - Paris ( ENS Paris ) -Centre National de la Recherche Scientifique ( CNRS ), Ghent University [Belgium] ( UGENT ), German Research Centre for Geosciences - Helmholtz-Centre Potsdam ( GFZ ), Laboratoire de recherche en Hydrodynamique, Énergétique et Environnement Atmosphérique ( LHEEA ), École Centrale de Nantes ( ECN ) -Centre National de la Recherche Scientifique ( CNRS ), Institut de Recherche en Génie Civil et Mécanique ( GeM ), Université de Nantes ( UN ) -École Centrale de Nantes ( ECN ) -Centre National de la Recherche Scientifique ( CNRS ), Neurorestoration Group, King‘s College London-Wolfson Centre for Age-related Diseases, Department of Computer Science [KAIST] ( CS ), Korea Advanced Institute of Science and Technology ( KAIST ), Laboratoire de l'Accélérateur Linéaire ( LAL ), Natl Engn Res Ctr Vegetables, Key Lab Biol & Genet Improvement Hort Crops N Chi, Beijing Acad Agr & Forestry Sci, University Hospital Puerta de Hierro, Madrid, Computational Science and Engineering Department [Daresbury] (STFC), Neuroépidémiologie Tropicale (NET), CHU Limoges-Institut d'Epidémiologie Neurologique et de Neurologie Tropicale-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut Génomique, Environnement, Immunité, Santé, Thérapeutique (GEIST), Université de Limoges (UNILIM)-Université de Limoges (UNILIM), Weill Cornell Medicine [Qatar], Maladies chroniques, santé perçue, et processus d'adaptation (APEMAC), Université Paris Descartes - Paris 5 (UPD5)-Université de Lorraine (UL), Cancéropôle du Grand Est-Institut National de la Santé et de la Recherche Médicale (INSERM), Centro de Estudios Avanzados en Zonas Aridas (CEAZA), Ecole Polytechnique Fédérale de Lausanne (EPFL), Laboratoire d'Ingénierie des Matériaux (LIM), Centre National de la Recherche Scientifique (CNRS), Lawrence Berkeley National Laboratory [Berkeley] (LBNL), Samsung Research &Development Institute India - Bangalore (Groupe Samsung) (SRI-B), Multimedia Research Center (MRC), University of Alberta, Division of Biostatistics (Biostat - MINNEAPOLIS), University of Minnesota [Twin Cities] (UMN), University of Minnesota System-University of Minnesota System, University of Southampton, University of Cambridge [UK] (CAM), Interactions, transferts, ruptures artistiques et culturels - EA 6301 (InTRu), Université de Tours (UT), Institut Jacques Monod (IJM (UMR_7592)), Université Paris Diderot - Paris 7 (UPD7)-Centre National de la Recherche Scientifique (CNRS), Stanford University, Unité de recherche Virologie et Immunologie Moléculaires (VIM (UR 0892)), Institut National de la Recherche Agronomique (INRA), National University of Singapore (NUS), Université Paris 1 Panthéon-Sorbonne - UFR Science Politique (UP1 UFR11), Université Paris 1 Panthéon-Sorbonne (UP1), National Diagnostics Centre (NDC), National University of Ireland [Galway] (NUI Galway), Arthritis Research UK Epidemiology Unit (MANCHESTER - Arthritis Research), Universidade do Porto = University of Porto, Advanced Laboratories on Embedded Systems [Roma] (ALES), Wageningen University and Research [Wageningen] (WUR), University of Oxford, Universitat Politècnica de Catalunya [Barcelona] (UPC), Institut National de Recherche et d'Analyse Physico-Chimique (INRAP), University of Connecticut (UCONN), Norwegian Institute for Air Research (NILU), Franche-Comté Électronique Mécanique, Thermique et Optique - Sciences et Technologies (UMR 6174) (FEMTO-ST), Université de Technologie de Belfort-Montbeliard (UTBM)-Ecole Nationale Supérieure de Mécanique et des Microtechniques (ENSMM)-Centre National de la Recherche Scientifique (CNRS)-Université de Franche-Comté (UFC), Université Bourgogne Franche-Comté [COMUE] (UBFC)-Université Bourgogne Franche-Comté [COMUE] (UBFC), University of Tehran, Friedrich-Alexander Universität Erlangen-Nürnberg (FAU), Sociétés, Acteurs, Gouvernement en Europe (SAGE), Université de Strasbourg (UNISTRA)-Centre National de la Recherche Scientifique (CNRS), The George Washington University (GW), Washington State University (WSU), Laboratoire de Physique de l'ENS Lyon (Phys-ENS), École normale supérieure de Lyon (ENS de Lyon)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Centre National de la Recherche Scientifique (CNRS), Institut de recherche en informatique de Toulouse (IRIT), Université Toulouse Capitole (UT Capitole), Université de Toulouse (UT)-Université de Toulouse (UT)-Université Toulouse - Jean Jaurès (UT2J), Université de Toulouse (UT)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Centre National de la Recherche Scientifique (CNRS)-Institut National Polytechnique (Toulouse) (Toulouse INP), Université de Toulouse (UT)-Toulouse Mind & Brain Institut (TMBI), Université Toulouse - Jean Jaurès (UT2J), Université de Toulouse (UT)-Université de Toulouse (UT)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT), Université Catholique de Louvain = Catholic University of Louvain (UCL), Div Cyclotron & Radiopharmaceut Sci (DRDO, INMAS), School of Physics and Astronomy [St Andrews], Tata Research Development and Design Center (TRDDC), MOLTECH-Anjou, Université d'Angers (UA)-Institut de Chimie du CNRS (INC)-Centre National de la Recherche Scientifique (CNRS), Helsingin yliopisto = Helsingfors universitet = University of Helsinki, Swedish Defense Research Agency (FOI), Centre de Recherche en Information Biomédicale sino-français (CRIBS), Université de Rennes (UR)-Southeast University [Jiangsu]-Institut National de la Santé et de la Recherche Médicale (INSERM), Laboratory of Image Science and Technology [Nanjing] (LIST), Laboratoire de glaciologie et géophysique de l'environnement (LGGE), Observatoire des Sciences de l'Univers de Grenoble (OSUG), Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut national des sciences de l'Univers (INSU - CNRS)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut national des sciences de l'Univers (INSU - CNRS)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS), Department of Mechanical and Automation Engineering (CAD Laboratory), Università degli studi di Bari Aldo Moro = University of Bari Aldo Moro (UNIBA), Heuristique et Diagnostic des Systèmes Complexes [Compiègne] (Heudiasyc), Université de Technologie de Compiègne (UTC)-Centre National de la Recherche Scientifique (CNRS), Biotechnology and Biological Sciences Research Council (BBSRC)-Biotechnology and Biological Sciences Research Council (BBSRC), Queen Mary University of London (QMUL), Centre d'économie de la Sorbonne (CES), Université Paris 1 Panthéon-Sorbonne (UP1)-Centre National de la Recherche Scientifique (CNRS), Paris School of Economics (PSE), Université Paris 1 Panthéon-Sorbonne (UP1)-École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-École des hautes études en sciences sociales (EHESS)-École des Ponts ParisTech (ENPC)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Istituto Dalle Molle di Studi sull'Intelligenza Artificiale (IDSIA), Università della Svizzera italiana = University of Italian Switzerland (USI)-Scuola universitaria professionale della Svizzera italiana = University of Applied Sciences and Arts of Southern Switzerland [Manno] (SUPSI), Pennsylvania State University (Penn State), Penn State System-Penn State System, Jet Propulsion Laboratory (JPL), NASA-California Institute of Technology (CALTECH), Hong Kong Baptist University (HKBU), Département Optique (OPT), Université européenne de Bretagne - European University of Brittany (UEB)-Télécom Bretagne-Institut Mines-Télécom [Paris] (IMT), Services répartis, Architectures, MOdélisation, Validation, Administration des Réseaux (SAMOVAR), Institut Mines-Télécom [Paris] (IMT)-Télécom SudParis (TSP), Département Réseaux et Services Multimédia Mobiles (TSP - RS2M), University of Melbourne, Organisation Mondiale de la Santé / World Health Organization Office (OMS / WHO), University of Otago [Dunedin, Nouvelle-Zélande], Center for TeleInFrastruktur (CTIF), Aalborg University [Denmark] (AAU), Savoirs, Textes, Langage (STL) - UMR 8163 (STL), Université de Lille-Centre National de la Recherche Scientifique (CNRS), Indian Institute of Technology Madras (IIT Madras), Universidade Estadual Paulista Júlio de Mesquita Filho = São Paulo State University (UNESP), Erasmus University Medical Center [Rotterdam] (Erasmus MC), Université Grenoble Alpes - UFR Médecine (UGA UFRM), Université Grenoble Alpes [2016-2019] (UGA [2016-2019]), German Cancer Research Center - Deutsches Krebsforschungszentrum [Heidelberg] (DKFZ), Institut Cochin (IC UM3 (UMR 8104 / U1016)), Université Paris Descartes - Paris 5 (UPD5)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), European Microsoft Innovation Center (EMIC), Laboratoire de Mécanique, Physique et Géosciences (LMPG), Université Le Havre Normandie (ULH), Normandie Université (NU)-Normandie Université (NU), Novartis Institute for Tropical Diseases (NITD), Institut de Génétique et de Biologie Moléculaire et Cellulaire (IGBMC), Université de Strasbourg (UNISTRA)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Center for Mathematical Modeling (CMM), Universidad de Chile = University of Chile [Santiago] (UCHILE), Laboratory for Atmospheric and Space Physics [Boulder] (LASP), University of Colorado [Boulder], University of Occupational and Environmental Health [Kitakyushu] (UEOH), Indian Institute of Technology Delhi (IIT Delhi), Institut de Recherche sur les Phénomènes Hors Equilibre (IRPHE), Aix Marseille Université (AMU)-École Centrale de Marseille (ECM)-Centre National de la Recherche Scientifique (CNRS), Yale University [New Haven]-Yale School of Medicine [New Haven, Connecticut] (YSM), Nanoscience Institute (NEST), University of Pisa - Università di Pisa, Laboratory Of Immune Cell Biology (LICB), National Institutes of Health [Bethesda] (NIH), Rheinische Friedrich-Wilhelms-Universität Bonn, Royal Institute of Technology [Stockholm] (KTH ), Institut für Informatik [München/Munich] (LMU), Ludwig-Maximilians-Universität München (LMU), National ICT Australia [Sydney] (NICTA), Institut d'Histoire et de Philosophie des Sciences et des Techniques (IHPST), Université Paris 1 Panthéon-Sorbonne (UP1)-Département d'Etudes Cognitives - ENS Paris (DEC), École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Centre National de la Recherche Scientifique (CNRS), Universiteit Gent = Ghent University (UGENT), German Research Centre for Geosciences - Helmholtz-Centre Potsdam (GFZ), Laboratoire de recherche en Hydrodynamique, Énergétique et Environnement Atmosphérique (LHEEA), École Centrale de Nantes (ECN)-Centre National de la Recherche Scientifique (CNRS), Institut de Recherche en Génie Civil et Mécanique (GeM), Université de Nantes - UFR des Sciences et des Techniques (UN UFR ST), Université de Nantes (UN)-Université de Nantes (UN)-École Centrale de Nantes (ECN)-Centre National de la Recherche Scientifique (CNRS), Department of Computer Science [KAIST] (CS), Korea Advanced Institute of Science and Technology (KAIST), Kardiyoloji, Institut Génomique, Environnement, Immunité, Santé, Thérapeutique (GEIST), Université de Limoges (UNILIM)-Université de Limoges (UNILIM)-CHU Limoges-Institut d'Epidémiologie Neurologique et de Neurologie Tropicale-Institut National de la Santé et de la Recherche Médicale (INSERM), University of Minnesota [Twin Cities], Centre National de la Recherche Scientifique (CNRS)-Université Paris Diderot - Paris 7 (UPD7), Unité de recherche Virologie et Immunologie Moléculaires (VIM), Université Panthéon-Sorbonne - UFR Science Politique (UP1 UFR11), Université Panthéon-Sorbonne (UP1), Wageningen University and Research Centre [Wageningen] (WUR), Institut National de Recherche et d'Analyse Physico-chimique (Ariana, Tunisie) (INRAP), Université de Franche-Comté (UFC)-Centre National de la Recherche Scientifique (CNRS)-Ecole Nationale Supérieure de Mécanique et des Microtechniques (ENSMM)-Université de Technologie de Belfort-Montbeliard (UTBM), George Washington University (GW), École normale supérieure - Lyon (ENS Lyon)-Université Claude Bernard Lyon 1 (UCBL), Université Toulouse 1 Capitole (UT1)-Université Toulouse - Jean Jaurès (UT2J)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées, Université Catholique de Louvain (UCL), MOLTECH-ANJOU (MOLTECH-ANJOU), Université d'Angers (UA)-Centre National de la Recherche Scientifique (CNRS), University of Helsinki, Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-Southeast University [Jiangsu]-Institut National de la Santé et de la Recherche Médicale (INSERM), Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Centre National de la Recherche Scientifique (CNRS), Université Panthéon-Sorbonne (UP1)-Centre National de la Recherche Scientifique (CNRS), Università della Svizzera italiana (USI)-Scuola universitaria professionale della Svizzera italiana [Manno] (SUPSI), California Institute of Technology (CALTECH)-NASA, Institut Mines-Télécom [Paris] (IMT)-Télécom SudParis (TSP)-Centre National de la Recherche Scientifique (CNRS), Département Réseaux et Services Multimédia Mobiles (RS2M), Universidade Estadual Paulista Júlio de Mesquita Filho [São José do Rio Preto] (UNESP), Université Grenoble Alpes (UGA), Universidad de Santiago de Chile [Santiago] (USACH), Yale University [New Haven]-Yale University School of Medicine, Université Panthéon-Sorbonne (UP1)-Centre National de la Recherche Scientifique (CNRS)-Département d'Etudes Cognitives - ENS Paris (DEC), École normale supérieure - Paris (ENS Paris)-École normale supérieure - Paris (ENS Paris), Ghent University [Belgium] (UGENT), Université de Nantes - Faculté des Sciences et des Techniques, Grelier, Elisabeth, Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Université Toulouse - Jean Jaurès (UT2J)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Toulouse Mind & Brain Institut (TMBI), Université Toulouse - Jean Jaurès (UT2J)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Université Toulouse III - Paul Sabatier (UT3), Universidade do Porto, Université de Technologie de Belfort-Montbeliard (UTBM)-Ecole Nationale Supérieure de Mécanique et des Microtechniques (ENSMM)-Université de Franche-Comté (UFC), Université Bourgogne Franche-Comté [COMUE] (UBFC)-Université Bourgogne Franche-Comté [COMUE] (UBFC)-Centre National de la Recherche Scientifique (CNRS), École normale supérieure - Lyon (ENS Lyon)-Centre National de la Recherche Scientifique (CNRS)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon, Université Toulouse 1 Capitole (UT1), Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire des Sciences de l'Univers de Grenoble (OSUG), Centre National de la Recherche Scientifique (CNRS)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry]), Università degli studi di Bari Aldo Moro (UNIBA), École des Ponts ParisTech (ENPC)-École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université Paris 1 Panthéon-Sorbonne (UP1)-Centre National de la Recherche Scientifique (CNRS)-École des hautes études en sciences sociales (EHESS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Università della Svizzera italiana = University of Italian Switzerland (USI)-Scuola universitaria professionale della Svizzera italiana [Manno] (SUPSI), Institut Mines-Télécom [Paris] (IMT)-Télécom Bretagne-Université européenne de Bretagne - European University of Brittany (UEB), Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Université de Strasbourg (UNISTRA), École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-École normale supérieure - Paris (ENS Paris), Universiteit Gent = Ghent University [Belgium] (UGENT), Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut d'Epidémiologie Neurologique et de Neurologie Tropicale-CHU Limoges-Institut Génomique, Environnement, Immunité, Santé, Thérapeutique (GEIST), Université de Franche-Comté (UFC), Université Bourgogne Franche-Comté [COMUE] (UBFC)-Université Bourgogne Franche-Comté [COMUE] (UBFC)-Ecole Nationale Supérieure de Mécanique et des Microtechniques (ENSMM)-Centre National de la Recherche Scientifique (CNRS)-Université de Technologie de Belfort-Montbeliard (UTBM), Institut de Chimie du CNRS (INC)-Université d'Angers (UA)-Centre National de la Recherche Scientifique (CNRS), Centre National de la Recherche Scientifique (CNRS)-Université Paris Descartes - Paris 5 (UPD5)-Institut National de la Santé et de la Recherche Médicale (INSERM), Centre National de la Recherche Scientifique (CNRS)-École Centrale de Nantes (ECN), Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut national des sciences de l'Univers (INSU - CNRS)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS), Wolfson Centre for Age-related Diseases-King‘s College London, Cell biology, Public Health, Epidemiology, Health Technology Assessment (HTA), Erasmus MC other, Pathology, and Cardiothoracic Surgery
Subjects: Gerontology, Male, CHANGING RELATION, Nutrition and Disease, MESH : Life Expectancy, MESH : Aged, ECONOMIC-DEVELOPMENT, Poison control, MESH: Global Health, Global Health, Socioeconomic Factor, Communicable Disease, MESH : Chronic Disease, Health Transition, Voeding en Ziekte, Quality-Adjusted Life Year, SELF-RATED HEALTH, MESH : Socioeconomic Factors, Medicine, MESH : Female, MESH: Mortality, Premature, 2. Zero hunger, MESH: Aged, education.field_of_study, MESH: Middle Aged, Mortality rate, Medicine (all), GBD2013 diseases, [ SDV.SPEE ] Life Sciences [q-bio]/Santé publique et épidémiologie, General Medicine, Middle Aged, 3. Good health, MESH : Wounds and Injuries, Epidemiological transition, MESH: Quality-Adjusted Life Years, MESH: Communicable Diseases, NONCOMMUNICABLE DISEASES, Female, Quality-Adjusted Life Years, MESH: Life Expectancy, MESH: Health Transition, Human, MESH: Socioeconomic Factors, ACUTE MYOCARDIAL-INFARCTION, MESH : Male, MORTALITY TRENDS, Population, MESH : Health Transition, Communicable Diseases, Article, Life Expectancy, EUROPEAN-UNION, SDG 3 - Good Health and Well-being, General & Internal Medicine, SYSTEMATIC ANALYSIS, Disability-adjusted life year, Humans, Life Science, MESH : Middle Aged, Mortality, education, Premature, MESH : Mortality, Premature, VLAG, Aged, MESH: Humans, business.industry, Mortality, Premature, MESH: Chronic Disease, MESH : Communicable Diseases, Wounds and Injurie, MESH : Humans, MESH : Quality-Adjusted Life Years, Non-communicable disease, Chronic Disease, Socioeconomic Factors, Wounds and Injuries, medicine.disease, MESH: Male, LOW SOCIOECONOMIC-STATUS, Years of potential life lost, [SDV.SPEE] Life Sciences [q-bio]/Santé publique et épidémiologie, MESH: Wounds and Injuries, Life expectancy, RISK-FACTORS, MESH : Global Health, [SDV.SPEE]Life Sciences [q-bio]/Santé publique et épidémiologie, business, MESH: Female, Demography
Abstract: Summary Background The Global Burden of Disease Study 2013 (GBD 2013) aims to bring together all available epidemiological data using a coherent measurement framework, standardised estimation methods, and transparent data sources to enable comparisons of health loss over time and across causes, age–sex groups, and countries. The GBD can be used to generate summary measures such as disability-adjusted life-years (DALYs) and healthy life expectancy (HALE) that make possible comparative assessments of broad epidemiological patterns across countries and time. These summary measures can also be used to quantify the component of variation in epidemiology that is related to sociodemographic development. Methods We used the published GBD 2013 data for age-specific mortality, years of life lost due to premature mortality (YLLs), and years lived with disability (YLDs) to calculate DALYs and HALE for 1990, 1995, 2000, 2005, 2010, and 2013 for 188 countries. We calculated HALE using the Sullivan method; 95% uncertainty intervals (UIs) represent uncertainty in age-specific death rates and YLDs per person for each country, age, sex, and year. We estimated DALYs for 306 causes for each country as the sum of YLLs and YLDs; 95% UIs represent uncertainty in YLL and YLD rates. We quantified patterns of the epidemiological transition with a composite indicator of sociodemographic status, which we constructed from income per person, average years of schooling after age 15 years, and the total fertility rate and mean age of the population. We applied hierarchical regression to DALY rates by cause across countries to decompose variance related to the sociodemographic status variable, country, and time. Findings Worldwide, from 1990 to 2013, life expectancy at birth rose by 6·2 years (95% UI 5·6–6·6), from 65·3 years (65·0–65·6) in 1990 to 71·5 years (71·0–71·9) in 2013, HALE at birth rose by 5·4 years (4·9–5·8), from 56·9 years (54·5–59·1) to 62·3 years (59·7–64·8), total DALYs fell by 3·6% (0·3–7·4), and age-standardised DALY rates per 100 000 people fell by 26·7% (24·6–29·1). For communicable, maternal, neonatal, and nutritional disorders, global DALY numbers, crude rates, and age-standardised rates have all declined between 1990 and 2013, whereas for non–communicable diseases, global DALYs have been increasing, DALY rates have remained nearly constant, and age-standardised DALY rates declined during the same period. From 2005 to 2013, the number of DALYs increased for most specific non-communicable diseases, including cardiovascular diseases and neoplasms, in addition to dengue, food-borne trematodes, and leishmaniasis; DALYs decreased for nearly all other causes. By 2013, the five leading causes of DALYs were ischaemic heart disease, lower respiratory infections, cerebrovascular disease, low back and neck pain, and road injuries. Sociodemographic status explained more than 50% of the variance between countries and over time for diarrhoea, lower respiratory infections, and other common infectious diseases; maternal disorders; neonatal disorders; nutritional deficiencies; other communicable, maternal, neonatal, and nutritional diseases; musculoskeletal disorders; and other non-communicable diseases. However, sociodemographic status explained less than 10% of the variance in DALY rates for cardiovascular diseases; chronic respiratory diseases; cirrhosis; diabetes, urogenital, blood, and endocrine diseases; unintentional injuries; and self-harm and interpersonal violence. Predictably, increased sociodemographic status was associated with a shift in burden from YLLs to YLDs, driven by declines in YLLs and increases in YLDs from musculoskeletal disorders, neurological disorders, and mental and substance use disorders. In most country-specific estimates, the increase in life expectancy was greater than that in HALE. Leading causes of DALYs are highly variable across countries. Interpretation Global health is improving. Population growth and ageing have driven up numbers of DALYs, but crude rates have remained relatively constant, showing that progress in health does not mean fewer demands on health systems. The notion of an epidemiological transition—in which increasing sociodemographic status brings structured change in disease burden—is useful, but there is tremendous variation in burden of disease that is not associated with sociodemographic status. This further underscores the need for country-specific assessments of DALYs and HALE to appropriately inform health policy decisions and attendant actions. Funding Bill & Melinda Gates Foundation. BACKGROUND: The Global Burden of Disease Study 2013 (GBD 2013) aims to bring together all available epidemiological data using a coherent measurement framework, standardised estimation methods, and transparent data sources to enable comparisons of health loss over time and across causes, age-sex groups, and countries. The GBD can be used to generate summary measures such as disability-adjusted life-years (DALYs) and healthy life expectancy (HALE) that make possible comparative assessments of broad epidemiological patterns across countries and time. These summary measures can also be used to quantify the component of variation in epidemiology that is related to sociodemographic development. METHODS: We used the published GBD 2013 data for age-specific mortality, years of life lost due to premature mortality (YLLs), and years lived with disability (YLDs) to calculate DALYs and HALE for 1990, 1995, 2000, 2005, 2010, and 2013 for 188 countries. We calculated HALE using the Sullivan method; 95% uncertainty intervals (UIs) represent uncertainty in age-specific death rates and YLDs per person for each country, age, sex, and year. We estimated DALYs for 306 causes for each country as the sum of YLLs and YLDs; 95% UIs represent uncertainty in YLL and YLD rates. We quantified patterns of the epidemiological transition with a composite indicator of sociodemographic status, which we constructed from income per person, average years of schooling after age 15 years, and the total fertility rate and mean age of the population. We applied hierarchical regression to DALY rates by cause across countries to decompose variance related to the sociodemographic status variable, country, and time. FINDINGS: Worldwide, from 1990 to 2013, life expectancy at birth rose by 6·2 years (95% UI 5·6-6·6), from 65·3 years (65·0-65·6) in 1990 to 71·5 years (71·0-71·9) in 2013, HALE at birth rose by 5·4 years (4·9-5·8), from 56·9 years (54·5-59·1) to 62·3 years (59·7-64·8), total DALYs fell by 3·6% (0·3-7·4), and age-standardised DALY rates per 100 000 people fell by 26·7% (24·6-29·1). For communicable, maternal, neonatal, and nutritional disorders, global DALY numbers, crude rates, and age-standardised rates have all declined between 1990 and 2013, whereas for non-communicable diseases, global DALYs have been increasing, DALY rates have remained nearly constant, and age-standardised DALY rates declined during the same period. From 2005 to 2013, the number of DALYs increased for most specific non-communicable diseases, including cardiovascular diseases and neoplasms, in addition to dengue, food-borne trematodes, and leishmaniasis; DALYs decreased for nearly all other causes. By 2013, the five leading causes of DALYs were ischaemic heart disease, lower respiratory infections, cerebrovascular disease, low back and neck pain, and road injuries. Sociodemographic status explained more than 50% of the variance between countries and over time for diarrhoea, lower respiratory infections, and other common infectious diseases; maternal disorders; neonatal disorders; nutritional deficiencies; other communicable, maternal, neonatal, and nutritional diseases; musculoskeletal disorders; and other non-communicable diseases. However, sociodemographic status explained less than 10% of the variance in DALY rates for cardiovascular diseases; chronic respiratory diseases; cirrhosis; diabetes, urogenital, blood, and endocrine diseases; unintentional injuries; and self-harm and interpersonal violence. Predictably, increased sociodemographic status was associated with a shift in burden from YLLs to YLDs, driven by declines in YLLs and increases in YLDs from musculoskeletal disorders, neurological disorders, and mental and substance use disorders. In most country-specific estimates, the increase in life expectancy was greater than that in HALE. Leading causes of DALYs are highly variable across countries. INTERPRETATION: Global health is improving. Population growth and ageing have driven up numbers of DALYs, but crude rates have remained relatively constant, showing that progress in health does not mean fewer demands on health systems. The notion of an epidemiological transition-in which increasing sociodemographic status brings structured change in disease burden-is useful, but there is tremendous variation in burden of disease that is not associated with sociodemographic status. This further underscores the need for country-specific assessments of DALYs and HALE to appropriately inform health policy decisions and attendant actions. FUNDING: Bill & Melinda Gates Foundation.
Published: 2015
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25 results on '"Richardus, Jan"'

1. A sharp decrease in reported non-COVID-19 notifiable infectious diseases during the first wave of the COVID-19 epidemic in the Rotterdam region, the Netherlands: a descriptive study.

2. Timeliness of notification systems for infectious diseases: A systematic literature review.

3. Public preferences for vaccination programmes during pandemics caused by pathogens transmitted through respiratory droplets - a discrete choice experiment in four European countries, 2013.

4. Global, regional, and national disability-adjusted life years (DALYs) for 306 diseases and injuries and healthy life expectancy (HALE) for 188 countries, 1990-2013: quantifying the epidemiological transition.

5. Acceptance of vaccinations in pandemic outbreaks: a discrete choice experiment.

6. A qualitative exploration of social contact patterns relevant to airborne infectious diseases in northwest Bangladesh.

7. Establishing a standard method for analysing case detection delay in leprosy using a Bayesian modelling approach.

8. Identifying clusters of leprosy patients in India: A comparison of methods.

9. Measuring endemicity and burden of leprosy across countries and regions: A systematic review and Delphi survey.

10. Number of people requiring post-exposure prophylaxis to end leprosy: A modeling study.

11. Minimum requirements and optimal testing strategies of a diagnostic test for leprosy as a tool towards zero transmission: A modeling study.

12. African Programme for Onchocerciasis Control 1995–2015: Model-Estimated Health Impact and Cost.

13. The Long Term Effect of Current and New Interventions on the New Case Detection of Leprosy: A Modeling Study.

14. The SARS epidemic in mainland China: bringing together all epidemiological data.

15. The impact of public health control measures during the SARS epidemic in mainland China.

16. Polymorphism N248S in the Human Toll-Like Receptor 1 Gene Is Related to Leprosy and Leprosy Reactions.

17. Risk Perceptions and Behaviour: Towards Pandemic Control of Emerging Infectious Diseases.

18. Perceived Threat, Risk Perception, and Efficacy Beliefs Related to SARS and Other (Emerging) Infectious Diseases: Results of an International Survey.

19. Physical Distance, Genetic Relationship, Age, and Leprosy Classification Are Independent Risk Factors for Leprosy in Contacts of Patients with Leprosy.

20. Black--White Differences in Infectious Disease Mortality in the United States.

21. Leprosy remains an important public health challenge in India.

22. Chapter Two - Mathematical Modelling of Leprosy and Its Control.

23. Management of Chlamydia Cases and Their Partners: Results From a Home-Based Screening Program Organized by Municipal Publlc Health Services With Referral to Regular Health Care.

24. The future incidence of leprosy:a scenario analysis.

25. Global, regional, and national disability-adjusted life years (DALYs) for 306 diseases and injuries and healthy life expectancy (HALE) for 188 countries, 1990-2013

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