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Executive SummaryThis document serves as an update and companion piece to the 2005 Society for Healthcare Epidemiology of America (SHEA) Position Paper entitled “Influenza Vaccination of Healthcare Workers and Vaccine Allocation for Healthcare Workers During Vaccine Shortages.” In large part, the discussion about the rationale for influenza vaccination of healthcare personnel (HCP), the strategies designed to improve influenza vaccination rates in this population, and the recommendations made in the 2005 paper still stand. This position paper notes new evidence released since publication of the 2005 paper and strengthens SHEA's position on the importance of influenza vaccination of HCP. This document does not discuss vaccine allocation during times of vaccine shortage, because the 2005 SHEA Position Paper still serves as the Society's official statement on that issue.

Monitoring multidrug-resistant organisms (MDROs) and the infections they cause in a healthcare setting is important to detect newly emerging antimicrobial resistance profiles, to identify vulnerable patient populations, and to assess the need for and effectiveness of interventions; however, it is unclear which metrics are the best, because most of the metrics are not standardized. This document describes useful and practical metrics and surveillance considerations for measuring MDROs and the infections they cause in the practice of infection prevention and control in healthcare settings. These metrics are designed to aid healthcare workers in documenting trends over time within their facility and should not be used for interfacility comparison.

Data on the extent of the burden due to schistosomiasis is sparse in most Sub-Saharan African countries. However, this data is crucial for triggering medical attention. A review of extent of morbidity and determinants associated with schistosomiasis in Malawi was therefore conducted to quantify the infection in order to concretise the need for medical intervention. A systematic and traditional search strategy was used to find literature for the review, whilst exclusion and inclusion criteria were used to identify appropriate articles. Logistic regression curves of epidemiological model Y = (a + bxc)/(1 + bxc) and the recommendation that schistosomiasis prevalence can be used to estimate morbidity were employed to quantify morbidity at various infection stages. Morbidity was quantified as a direct proportion of the population and the respective national schistosomiasis prevalence. Findings showed that both S. mansoni and S. haematobium are present in Malawi with the latter highly prevalent (50%). Furthermore, out of the estimated population of 16,829 million, approximately 8.4 million have schistosomiasis, with about 4.4 million of these aged 18 years and below. The most frequent manifestation is Katayama syndrome, while ascites is the lowest, impacting about 3.0 million and 960 individuals, respectively. Localised studies on association of schistosomiasis infection to risk factors such as occupation, age and gender found odds ratio (OR) ranging from 1.29 to 5.37. Morbidity due to schistosomiasis is high in Malawi. It is therefore recommended that a more detailed study on the determinants of high schistosomiasis and re-evaluation of the current control measures be conducted if the current morbidity statistics are to be remarkably reduced. Electronic supplementary material The online version of this article (doi:10.1186/s40249-015-0053-1) contains supplementary material, which is available to authorized users.

Human echinococcosis remains a very serious public health problem worldwide, although a decline in incidence has been observed in some endemic areas during the last decades. However, in some non-endemic areas an increase in new cases and new foci of animal echinococcosis were registered during the same time. In Dalmatia, a well known endemic area of hydatidosis in the most Mediterranean part of Croatia, from the mid-1950s until present a decrease of incidence of over 70% has been registered. Age, sex and occupational category specific incidence as well as lethality rate have remained the same as before. Migrations from rural to urban regions seem to be the most important parameter in the changing epidemiology of human hydatidosis in Dalmatia.

We describe the response to detection of a time–space cluster of new HIV infection in the Portland, OR metro area among people who inject drugs (PWID) and/or people who use any form of methamphetamine. This time–space cluster took place in a region with a syndemic of homelessness and drug use. The investigation included new HIV diagnoses in 2018, 2019, and 2020 in Clackamas, Multnomah, and Washington Counties. Public health response included activating incident command, development and implementation of an enhanced interview tool, outreach testing, and stakeholder engagement. We identified 396 new cases of HIV infection, 116 (29%) of which met the cluster definition. Most cluster cases had no molecular relationships to previous cases. Persons responding to the enhanced interview tool reported behaviors associated with HIV acquisition. Field outreach testing did not identify any new HIV cases but did identify hepatitis C and syphilis infections. We show the importance of a robust public health response to a time–space cluster of new HIV infections in an urban area.

BackgroundImmigration is a determinant of tuberculosis (TB) epidemiology. The US-Mexican border state of Tamaulipas serves as a migration waypoint for further immigration to the US, and has the second highest incidence of TB in Mexico. Here, we determined the contribution and characteristics of immigrants to the TB burden in Tamaulipas.MethodsTB surveillance data from Tamaulipas (2006-2013) was used to conduct a cross-sectional characterization of TB immigrants (born outside Tamaulipas) and identify their association with TB treatment outcomes.ResultsImmigrants comprised 30.8% of the TB patients, with >99% originating from internal Mexican migration. Most migration was from South to North, with cities adjacent to the US border as destinations. Immigrants had higher odds of risk factors for TB [older age (≥ 65 yr old, OR 2.4, 95% CI 2.1, 2.8), low education (OR 1.3, 95% CI 1.2, 1.4), diabetes (OR 1.2, 95% CI 1.1, 1.4)], or abandoning TB treatment (adjusted OR 1.2, 95% CI 1.0, 1.5).ConclusionsThe US port of entry of Tamaulipas has a predominant south to north migration, positively impacting TB prevalence in this region. There is a need to identify strategies to prevent and manage TB more effectively in this Mexican migration waypoint.

Drug overdose remains a leading cause of death in the US, with growing rates attributable to illicit fentanyl use. Recent HIV outbreaks among people who inject drugs (PWID) and service disruptions from COVID-19 have renewed concerns on HIV resurgence. We examined the relationship between fentanyl use and three injection-related HIV risk behaviors among PWID in Baltimore City (BC) and Anne Arundel Country (AAC), Maryland. PWID (N = 283) were recruited to the study through targeted sampling at street-based locations in BC and AAC from July 2018 to March 2020. Receptive syringe sharing (RSS) [adjusted odds ratio (AOR): 2.8, 95% confidence interval (CI): 1.2-6.3] and daily injecting (AOR: 1.9, 95% CI: 1.0-3.6) were associated with injecting fentanyl and cocaine together. Fentanyl availability and COVID-19 bring new HIV prevention challenges, particularly among those who inject fentanyl with cocaine, highlighting the importance to expand and sustain harm reduction, prevention, and treatment services for PWID to reduce HIV and overdose burden.

HIV incidence in sub-Saharan Africa declined substantially between 2000 and 2015. In this analysis, we consider the relative associations of nine structural and individual determinants with this decline. A linear mixed effects model of logged HIV incidence rates versus determinants was used. The data were from mathematical modelling as part of the 2019 Global Burden of Disease Study in 43 sub-Saharan African countries. We used forwards selection to determine a single final model of HIV incidence rate. The association of economic variables and HIV knowledge with incidence was found to be driven by education, while ART coverage had the largest impact on other determinants’ coefficients. In the final model, education years per capita contributed the most to explaining variation in HIV incidence rates; a 1-year increase in mean education years was associated with a 0.39 (− 0.56; − 0.2, t = − 4.48 p

Indonesia’s HIV epidemic is concentrated among key populations. While prevalence among men who have sex with men (MSM) is high, transmission among young MSM (15–24-years-old) remains poorly understood. We conducted a respondent driven sampling survey of 211 young MSM in urban Bandung, Indonesia in 2018–2019 to estimate HIV prevalence and associated risk factors. Thirty percent of young MSM were HIV antibody positive. This is nearly 100-fold greater than Indonesia’s population prevalence and sevenfold higher than average estimates for young MSM across Asia and the Pacific Region. Individual risk factors associated with HIV infection were being 20–24 years old, having a steady partner and preferring the receptive position during sex. Issues of stigma, discrimination and social exclusion were common. Few young MSM who were open with friends and family members about their sexual identity. Among those that were, close to half reported experiencing feelings of aversion from these groups. Wider structural factors that reduce social tolerance, restrict the rights of young MSM and compel concealment of sexual identity are likely to fuel high-risk behaviors and limit access to essential testing care and support services including pre-exposure prophylaxis which is not yet widely available. Urgent health, social, legal and political actions are required to respond to these factors and reduce the disproportionate contribution of young MSM to Indonesia’s HIV epidemic. Supplementary Information The online version contains supplementary material available at 10.1007/s10461-021-03347-0.

Cholera is one of the major public health problems in the state of Odisha, India since centuries. The current paper is a comprehensive report on epidemiology of cholera in Odisha, which was documented from 1993. PubMed and Web of Knowledge were searched for publications reporting cholera in Odisha during the period 1993–2015. The search was performed using the keywords ‘Odisha’ and/or ‘Orissa’ and ‘Cholera’. In addition, manual search was undertaken to find out relevant papers. During the study period, a total of 37 cholera outbreaks were reported with an average of >1.5 cholera outbreaks per year and case fatality ratio was 0.3%. Vibrio cholerae O1 Ogawa serotype was the major causative agent in most of the cholera cases. The recent studies demonstrated the prevalence of V. cholerae O1, El Tor variants carrying ctxB1, ctxB7 and Haitian variant tcpA allele associated with polymyxin B sensitivity and these variants are replacing the proto type El Tor. The first report of variant ctxB7 in Odisha during super-cyclone 1999 predicted its emergence and subsequent spread causing cholera outbreaks. The prevalence of multidrug-resistant V. cholerae at different time periods created alarming situation. The efficacy trial of oral cholera vaccine (OCV, Shanchol) in a public health set-up in Odisha has shown encouraging results which should be deployed for community level vaccination among the vulnerable population. This paper has taken an effort to disseminate the valuable information of epidemiology of cholera that will influence the policy-makers and epidemiologists for constant surveillance in other parts of Odisha, India and around the globe.

Acculturation may limit HIV-positive Asian Americans' active interactions with patient-healthcare providers (HCP) and utilization of HIV healthcare services; however, the specific mediation effect of acculturation still unknown. A bias-corrected factor score path analysis was performed to examine the proposed model of relations among acculturation, stigma, stress, and patient-HCP relationships. A convenience sample of 69 HIV-positive Asian Americans in San Francisco, Los Angeles, and New York City were recruited and collect data were collected on demographics, HIV-related stigma, stress, and patient-HCP relationships. HIV stigma and stress had a direct, negative effect on patient-HCP relationships. Acculturation had a positive total effect on patient-HCP relationships, and was mediated by HIV stigma and stress. A acculturation also had a direct impact on stigma and stress. Acculturation, HIV-related stigma, and stress are key elements to achieving good patient-HCP relationships, and provide insights on the design of culturally sensitive interventions to improve patient-HCP relationships.

We quantified the potential impact of different social distancing and self-isolation scenarios on the coronavirus disease 2019 (COVID-19) pandemic trajectory in Saudi Arabia and compared the modelling results to the confirmed epidemic trajectory. Using the susceptible, exposed, infected, quarantined and self-isolated, requiring hospitalisation, recovered/immune individuals, fatalities model, we assessed the impact of a non-pharmacological interventions’ subset. An unmitigated scenario (baseline), mitigation scenarios (25% reduction in social contact/twofold increase in self-isolation) and enhanced mitigation scenarios (50% reduction in social contact/twofold increase in self-isolation) were assessed and compared to the actual epidemic trajectory. For the unmitigated scenario, mitigation scenarios, enhanced mitigation scenarios and actual observed epidemic, the peak daily incidence rates (per 10 000 population) were 77.00, 16.00, 9.00 and 1.14 on days 71, 54, 35 and 136, respectively. The peak fatality rates were 35.00, 13.00, 5.00 and 0.016 on days 150, 125, 60 and 155, respectively. The R0 was 1.15, 1.14, 1.22 and 2.50, respectively. Aggressive implementation of social distancing and self-isolation contributed to the downward trend of the disease. We recommend using extensive models that comprehensively consider the natural history of COVID-19, social and behavioural patterns, age-specific data, actual network topology and population to elucidate the epidemic's magnitude and trajectory.

Ever since the World Health Organization (WHO) declared the new coronavirus disease 2019 (COVID-19) as a pandemic, there has been a public health debate concerning medical resources and supplies including hospital beds, intensive care units (ICU), ventilators and protective personal equipment (PPE). Forecasting COVID-19 dissemination has played a key role in informing healthcare professionals and governments on how to manage overburdened healthcare systems. However, forecasting during the pandemic remained challenging and sometimes highly controversial. Here, we highlight this challenge by performing a comparative evaluation for the estimations obtained from three COVID-19 surge calculators under different social distancing approaches, taking Lebanon as a case study. Despite discrepancies in estimations, the three surge calculators used herein agree that there will be a relative shortage in the capacity of medical resources and a significant surge in PPE demand if the social distancing policy is removed. Our results underscore the importance of implementing containment interventions including social distancing in alleviating the demand for medical care during the COVID-19 pandemic in the absence of any medication or vaccine. The paper also highlights the value of employing several models in surge planning.

The effectiveness of screening travellers during times of international disease outbreak is contentious, especially as the reduction in the risk of disease importation can be very small. Border screening typically consists of travellers being thermally scanned for signs of fever and/or completing a survey declaring any possible symptoms prior to admission to their destination country; while more thorough testing typically exists, these would generally prove more disruptive to deploy. In this paper, we describe a simple Monte Carlo based model that incorporates the epidemiology of coronavirus disease-2019 (COVID-19) to investigate the potential decrease in risk of disease importation that might be achieved by requiring travellers to undergo screening upon arrival during the current pandemic. This is a purely theoretical study to investigate the maximum impact that might be attained by deploying a test or testing programme simply at the point of entry, through which we may assess such action in the real world as a method of decreasing the risk of importation. We, therefore, assume ideal conditions such as 100% compliance among travellers and the use of a ‘perfect’ test. In addition to COVID-19, we also apply the presented model to simulated outbreaks of influenza, severe acute respiratory syndrome (SARS) and Ebola for comparison. Our model only considers screening implemented at airports, being the predominant method of international travel. Primary results showed that in the best-case scenario, screening at the point of entry may detect a maximum of 8.8% of travellers infected with COVID-19, compared to 34.8.%, 9.7% and 3.0% for travellers infected with influenza, SARS and Ebola respectively. While results appear to indicate that screening is more effective at preventing disease ingress when the disease in question has a shorter average incubation period, our results suggest that screening at the point of entry alone does not represent a sufficient method to adequately protect a nation from the importation of COVID-19 cases.

The severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2) is highly contagious, and the coronavirus disease 2019 (COVID-19) pandemic caused by it has forced many countries to adopt ‘lockdown’ measures to prevent the spread of the epidemic through social isolation of citizens. Some countries proposed universal mask wearing as a protection measure of public health to strengthen national prevention efforts and to limit the wider spread of the epidemic. In order to reveal the epidemic prevention efficacy of masks, this paper systematically evaluates the experimental studies of various masks and filter materials, summarises the general characteristics of the filtration efficiency of isolation masks with particle size, and reveals the actual efficacy of masks by combining the volume distribution characteristics of human exhaled droplets with different particle sizes and the SARS-CoV-2 virus load of nasopharynx and throat swabs from patients. The existing measured data show that the filtration efficiency of all kinds of masks for large particles and extra-large droplets is close to 100%. From the perspective of filtering the total number of pathogens discharged in the environment and protecting vulnerable individuals from breathing live viruses, the mask has a higher protective effect. If considering the weighted average filtration efficiency with different particle sizes, the filtration efficiencies of the N95 mask and the ordinary mask are 99.4% and 98.5%, respectively. The mask can avoid releasing active viruses to the environment from the source of infection, thus maximising the protection of vulnerable individuals by reducing the probability of inhaling a virus. Therefore, if the whole society strictly implements the policy of publicly wearing masks, the risk of large-scale spread of the epidemic can be greatly reduced. Compared with the overall cost of social isolation, limited personal freedoms and forced suspension of economic activities, the inconvenience for citizens caused by wearing masks is perfectly acceptable.

In this paper, we present a method to estimate the risk of reopening of schools illustrated with the case of the State of São Paulo, Brazil. The model showed that, although no death of children would result from the reopening of the schools in the three cities analysed, the risk of asymptomatic and symptomatic cases and secondary cases among teachers, school staff and relatives of the children is not negligible. Although the epidemic hit different regions with different intensities, our model shows that, for regions where the incidence profile is similar to the cities analysed, the risk of reopening of schools is still too high. This in spite of the fact that incidences in these cities were declining in the period of the time considered. Therefore, although we cannot extend the result to the entire country, the overall conclusion is valid for regions with a declining incidence and it is even more valid for regions where incidence is increasing. We assumed a very conservative level of infection transmissibility of children of just 10% as that of adults. In spite of the very low level of transmissibility is assumed, the number of secondary cases caused by infected children among teachers, school staff and relatives varied from 2 to 85. It is, therefore, too soon to have any degree of confidence that reopening of schools before the advent of a vaccine is the right decision to take. The purpose of our model and simulations is to provide a method to estimate the risk of school reopening, although we are sure it could be applied as a guide to public health strategies.

Vaccine hesitancy remains a serious global threat to achieve herd immunity, and this study aimed to assess the magnitude and associated factors of coronavirus disease-19 (COVID-19) vaccine hesitancy among healthcare workers (HCWs) in Amhara regional referral hospitals. A web-based anonymised survey was conducted among 440 HCWs in the Amhara region referral hospitals. The questionnaire was designed using Google Forms and distributed using telegram and e-mail from 15 May to 10 June 2021 to the randomly selected participants in each hospital. The data were analysed with Stata 14.0 and described using frequency tables. A multivariable binary logistic regression model was fitted and model fitness was checked with the Hosmer–Lemeshow goodness of fit test. Out of 440 participants, 418 were willing to participate in the study and the mean age was about 30 years. Overall, 45.9% (n = 192) of participants reported vaccine hesitancy. After applying multivariate analysis, age ≤25 years (adjusted odds ratio (aOR) = 5.6); do not wear a mask (aOR = 2.4); not compliance with physical distancing (aOR = 3.6); unclear information by public health authorities (aOR = 2.5); low risk of getting COVID-19 infection (aOR = 2.8); and not sure about the tolerability of the vaccine (aOR = 3.76) were associated with COVID-19 vaccine hesitancy. A considerable proportion of HCWs were hesitant towards COVID-19 vaccine, and this can be tackled with the provision of clear information about the vaccine.

Experience gained from responding to major outbreaks may have influenced the early coronavirus disease-2019 (COVID-19) pandemic response in several countries across Africa. We retrospectively assessed whether Guinea, Liberia and Sierra Leone, the three West African countries at the epicentre of the 2014–2016 Ebola virus disease outbreak, leveraged the lessons learned in responding to COVID-19 following the World Health Organization's (WHO) declaration of a public health emergency of international concern (PHEIC). We found relatively lower incidence rates across the three countries compared to many parts of the globe. Time to case reporting and laboratory confirmation also varied, with Guinea and Liberia reporting significant delays compared to Sierra Leone. Most of the selected readiness measures were instituted before confirmation of the first case and response measures were initiated rapidly after the outbreak confirmation. We conclude that the rapid readiness and response measures instituted by the three countries can be attributed to their lessons learned from the devastating Ebola outbreak, although persistent health systems weaknesses and the unique nature of COVID-19 continue to challenge control efforts.

Evidence that more people in some countries and fewer in others are dying because of the pandemic, than is reflected by reported Covid-19 mortality rates, is derived from mortality data. Worldwide, mortality data is used to estimate the full extent of the effects of the Covid-19 pandemic, both direct and indirect; the possible short fall in the number of cases reported to the WHO; and to suggest explanations for differences between countries. Excess mortality data is largely varying across countries and is not directly proportional to Covid-19 mortality. Using publicly available databases, deaths attributed to Covid-19 in 2020 and all deaths for the years 2015-2020 were tabulated for 36 countries together with economic, health, demographic, and government response stringency index variables. Residual death rates in 2020 were calculated as excess deaths minus death rates due to Covid-19 where excess deaths were observed deaths in 2020 minus the average for 2015-2019. For about half the countries, residual deaths were negative and for half, positive. The absolute rates in some countries were double those in others. In a regression analysis, the stringency index (p=0.026) was positively associated with residual mortality. There was no evidence of spatial clustering of residual mortality. The results show that published data on mortality from Covid-19 cannot be directly comparable across countries, likely due to differences in Covid-19 death reporting. In addition, the unprecedented public health measures implemented to control the pandemic may have produced either increased or reduced excess deaths due to other diseases. Further data on cause-specific mortality is required to determine the extent to which residual mortality represents non-Covid-19 deaths and to explain differences between countries.

The objective of this study was to describe the epidemiology of COVID-19 in Nigeria with a view of generating evidence to enhance planning and response strategies. A national surveillance dataset between 27 February and 6 June 2020 was retrospectively analysed, with confirmatory testing for COVID-19 done by real-time polymerase chain reaction (RT-PCR). The primary outcomes were cumulative incidence (CI) and case fatality (CF). A total of 40 926 persons (67% of total 60 839) had complete records of RT-PCR test across 35 states and the Federal Capital Territory, 12 289 (30.0%) of whom were confirmed COVID-19 cases. Of those confirmed cases, 3467 (28.2%) had complete records of clinical outcome (alive or dead), 342 (9.9%) of which died. The overall CI and CF were 5.6 per 100 000 population and 2.8%, respectively. The highest proportion of COVID-19 cases and deaths were recorded in persons aged 31–40 years (25.5%) and 61–70 years (26.6%), respectively; and males accounted for a higher proportion of confirmed cases (65.8%) and deaths (79.0%). Sixty-six per cent of confirmed COVID-19 cases were asymptomatic at diagnosis. In conclusion, this paper has provided an insight into the early epidemiology of COVID-19 in Nigeria, which could be useful for contextualising public health planning.

For outbreaks of gastrointestinal disease, rapid identification of the source is crucial to enable public health intervention and prevent further cases. Outbreak investigation comprises analyses of exposure information from cases and, if required, undertaking analytical epidemiological studies. Hypothesis generation has been reliant on empirical knowledge of exposures historically associated with a given pathogen. Epidemiology studies are resource-intensive and prone to bias, one of the reasons being the difficulties in recruiting appropriate controls. For this paper, the information from cases was compared against pre-defined background exposure information. As exemplars, three past outbreaks were used, one of common and two of rare exposures. Information from historical case trawling questionnaires was used to define background exposure having removed any exposures implicated with the outbreak. The case-background approach showed good sensitivity and specificity, identifying correctly all outbreak-related exposures. One additional exposure related to a retailer was identified and four food items where all cases had been exposed. In conclusion, the case-background method, a development of the case-case design, can be used to assist with hypothesis generation or when a case-control study may not be possible to carry out.

The outbreak of novel coronavirus pneumonia (coronavirus disease 2019 (COVID-19)), declared as a ‘global pandemic’ by the World Health Organization (WHO), is a public health emergency of international concern (PHEIC). The outbreak in multiple locations shows a trend of accelerating spread around the world. China has taken a series of powerful measures to contain the spread of the novel coronavirus. In response to the COVID-19 pandemic, in addition to actively finding effective treatment drugs and developing vaccines, it is more important to identify the source of infection at the community level as soon as possible to block the transmission path of the virus to prevent the spread of the pandemic. The implementation of grid management in the community and the adoption of precise management and control measures to reduce unnecessary personnel movement can effectively reduce the risk of pandemic spread. This paper mainly describes that the grid management mode can promote the refinement and comprehensiveness of community management. As a management system with potential to improve the governance ability of community affairs, it may be helpful to strengthen the prevention and control of the epidemic in the community.

We acknowledge funding from the UK Research and Innovation Global Challenge Research Fund (GCRF) (Grant Ref: ES/ T010487/1), the Conrad N. Hilton Foundation, the Bill and Melinda Gates Foundation, the Elisabeth Blackwell Institute for Health Research and the Beatriu de Pinós fellowship programme. The feasibility of non-pharmacological interventions (NPIs) such as physical distancing or isolation at home to prevent Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) transmission in low-resource countries is unknown. Household survey data from 54 African countries were used to investigate the feasibility of SARS-CoV-2 NPIs in low-resource settings. Across the 54 countries, approximately 718 million people lived in households with ≥6 individuals at home (median percentage of at-risk households 56% (95% confidence interval (CI), 51% to 60%)). Approximately 283 million people lived in households where ≥3 people slept in a single room (median percentage of at-risk households 15% (95% CI, 13% to 19%)). An estimated 890 million Africans lack on-site water (71% (95% CI, 62% to 80%)), while 700 million people lacked in-home soap/washing facilities (56% (95% CI, 42% to 73%)). The median percentage of people without a refrigerator in the home was 79% (95% CI, 67% to 88%), while 45% (95% CI, 39% to 52%) shared toilet facilites with other households. Individuals in low-resource settings have substantial obstacles to implementing NPIs for mitigating SARSCoV-2 transmission. These populations urgently need to be prioritized for COVID-19 vaccination to prevent disease and to contain the global pandemic.

An outbreak surveillance system for Salmonella integrating whole genome sequencing (WGS) and epidemiological data was developed in South East and London in 2016–17 to assess local WGS clusters for triage and investigation. Cases genetically linked within a 5 single-nucleotide polymorphism (SNP) single linkage cluster were assessed using a set of locally agreed thresholds based on time, person and place, for reporting to local health protection teams (HPTs). Between September 2016 and September 2017, 230 unique 5-SNP clusters (442 weekly reports) of non-typhoidal Salmonella 5-SNP WGS clusters were identified, of which 208 unique 5-SNP clusters (316 weekly reports) were not reported to the HPTs. In the remaining 22 unique clusters (126 weekly clusters) reported to HPTs, nine were known active outbreak investigations, seven were below locally agreed thresholds and six exceeded local thresholds. A common source or vehicle was identified in four of six clusters that exceeded locally agreed thresholds. This work demonstrates that a threshold-based surveillance system, taking into account time, place and genetic relatedness, is feasible and effective in directing the use of local public health resources for risk assessment and investigation of non-typhoidal Salmonella clusters.

Emerging diseases of zoonotic origin such as COVID-19 are a continuing public health threat in China that lead to a significant socioeconomic burden. This study reviewed the current laws and regulations, government reports and policy documents, and existing literature on zoonotic disease preparedness and prevention across the forestry, agriculture, and public health authorities in China, to articulate the current landscape of potential risks, existing mandates, and gaps. A total of 55 known zoonotic diseases (59 pathogens) are routinely monitored under a multi-sectoral system among humans and domestic and wild animals in China. These diseases have been detected in wild mammals, birds, reptiles, amphibians, and fish or other aquatic animals, the majority of which are transmitted between humans and animals via direct or indirect contact and vectors. However, this current monitoring system covers a limited scope of disease threats and animal host species, warranting expanded review for sources of disease and pathogen with zoonotic potential. In addition, the governance of wild animal protection and utilization and limited knowledge about wild animal trade value chains present challenges for zoonotic disease risk assessment and monitoring, and affect the completeness of mandates and enforcement. A coordinated and collaborative mechanism among different departments is required for the effective monitoring and management of disease emergence and transmission risks in the animal value chains. Moreover, pathogen surveillance among wild animal hosts and human populations outside of the routine monitoring system will fill the data gaps and improve our understanding of future emerging zoonotic threats to achieve disease prevention. The findings and recommendations will advance One Health collaboration across government and non-government stakeholders to optimize monitoring and surveillance, risk management, and emergency responses to known and novel zoonotic threats, and support COVID-19 recovery efforts., Highlights • Zoonotic diseases are managed by multiple government authorities in China. • Coverage of zoonotic diseases and wild animal hosts for risk monitoring is limited. • Wild animal governance poses challenges for zoonotic risk monitoring and reduction. • Coordinated and collaborative monitoring and surveillance systems are needed. • One Health approach has the potential to substantially address the existing gaps.

Antibiotic resistance (ABR) threatens the effectiveness of infectious disease treatments and contributes to increasing global morbidity and mortality. In this study, we systematically reviewed the identified risk factors for ABR among people in the healthcare system of mainland China. Five databases were systematically searched to identify relevant articles published in either English and Chinese between 1 January 2003 and 30 June 2019. A total of 176 facility-based references were reviewed for this study, ranging across 31 provinces in mainland China and reporting information from over 50 000 patients. Four major ABR risk factor domains were identified: (1) sociodemographic factors (includes migrant status, low income and urban residence), (2) patient clinical information (includes disease status and certain laboratory results), (3) admission to healthcare settings (includes length of hospitalisation and performance of invasive procedures) and (4) drug exposure (includes current or prior antibiotic therapy). ABR constitutes an ongoing major public health challenge in China. The healthcare sector-associated risk factors was the most important aspect identified in this review and need to be addressed. Primary health care system and ABR surveillance networks need to be further strengthened to prevent and control the communicable diseases, over-prescription and overuse of antibiotics.

Dog bites are a recognized public health issue due to their impact on human and animal health/welfare. This study aimed to investigate demographic and geographic disparities in the epidemiology of dog bites presentations reported to the emergency departments of the four main public hospitals in the Metro South region of Brisbane, Queensland, Australia. Dog bite patient hospitalization data geolocated to the street address were collected from clinical records management systems from the four main public hospitals in the Metro South Hospital Health Service region of Queensland for a 5-year period (ie. 01/07/2013 to 30/06/2017). We investigated the epidemiology of three clinical outcomes including probability of paediatric cases (paediatric vs. adult), probability of dog bites to the head (head injury vs. other injury), and probability of re-presentation to the ED following their initial dog bite (yes or no) by way of univariable then multivariable Bernoulli logistic regression models including patient postcode as a random effect. Residual semivariograms were created to identify spatial trends in the medical geography of dog bites and binomial geostatistical models were created to predict the probability of the outcomes of interest in Brisbane Metro south and surrounding suburbs. Our results demonstrate that compared to adult dog bite cases, paediatric dog bite cases were significantly associated with bites to the head or face or neck (OR 14.65, P

For some well-known pathogens like influenza or RSV, diagnostic and epidemiological data is available and continuously complement each other. For most other pathogens however, data is not always available or severely delayed. Furthermore, clinical data is needed to assess the burden of disease, which will enhance awareness and help to gain knowledge on emerging pathogens. In this position paper, we discuss the interdependence of diagnostics and epidemiology from a European perspective. In 2004, the European Centre for Disease Prevention and Control (ECDC) was founded to coordinate European wide surveillance and control. At present however, the ECDC still relies on university hospitals, public health institutions and other diagnostic institutions. Close collaboration between all stakeholders across Europe is therefore complex, but necessary to optimize the system for the individual patient. From the diagnostic side, data on detected pathogens should be shared with relevant health institutions in real-time. From the public health side, collected information should be made accessible for diagnostic and clinical institutions in real-time. Subsequently, this information needs to be disseminated across relevant medical disciplines to reach its full potential.

The rapid transmissibility of the severe acute respiratory syndrome-coronavirus-2 causing coronavirus disease-2019, requires timely dissemination of information and public health responses, with all 47 countries of the WHO African Region simultaneously facing significant risk, in contrast to the usual highly localised infectious disease outbreaks. This demanded a different approach to information management and an adaptive information strategy was implemented, focusing on data collection and management, reporting and analysis at the national and regional levels. This approach used frugal innovation, building on tools and technologies that are commonly used, and well understood; as well as developing simple, practical, highly functional and agile solutions that could be rapidly and remotely implemented, and flexible enough to be recalibrated and adapted as required. While the approach was successful in its aim of allowing the WHO Regional Office for Africa (WHO AFRO) to gather surveillance and epidemiological data, several challenges were encountered that affected timeliness and quality of data captured and reported by the member states, showing that strengthening data systems and digital capacity, and encouraging openness and data sharing are an important component of health system strengthening.

Adolescent girls and young women (AGYW) remain underserved and at risk for HIV acquisition in Ethiopia. However, there is significant risk heterogeneity among AGYW with limited consensus on optimal strategies of identifying vulnerable AGYW. This study assessed the utility of venue-based sampling approaches to identify AGYW at increased risk for HIV infection. Venue mapping and time-location-sampling (TLS) methods were used to recruit AGYW from three sub-cities of Addis Ababa, February–June 2018. Interviewer-administered surveys captured socio-demographic and behavioral characteristics. Measures of AGYW vulnerability were assessed geographically and described by venue type. A total of 2468 unique venues were identified, of which 802 (32%) were systematically selected for validation and 371 (46%) were eligible including many sites that would traditionally not be included as venues in need of HIV prevention services. Overall, 800 AGYW were enrolled across 81 sampled venues. AGYW reached were largely out-of-school (n = 599, 75%) with high proportions of AGYW reporting transactional sex (n = 101, 12.6%), food insecurity (n = 165, 20.7%) and migration (n = 565, 70.6%). Taken together, these data suggest the utility of TLS methods in reaching vulnerable, out-of-school AGYW in Addis Ababa, Ethiopia. Electronic supplementary material The online version of this article (10.1007/s10461-019-02537-1) contains supplementary material, which is available to authorized users.

Since the 1980s, dengue incidence has increased 30-fold. However, in 2017, there was a noticeable reduction in reported dengue incidence cases within the Americas, including severe and fatal cases. Understanding the mechanism underlying dengue's incidence and decline in the Americas is vital for public health planning. We aimed to provide plausible explanations for the decline in 2017.An expert panel of representatives from scientific and academic institutions, Ministry of Health officials from Latin America and PAHO/WHO staff met in October 2017 to propose hypotheses. The meeting employed six moderated plenary discussions in which participants reviewed epidemiological evidence, suggested explanatory hypotheses, offered their expert opinions on each and developed a consensus.The expert group established that in 2017, there was a generalised decreased incidence, severity and number of deaths due to dengue in the Americas, accompanied by a reduction in reported cases of both Zika and chikungunya virus infections, with no change in distribution among age groups affected. This decline was determined to be unlikely due to changes in epidemiological surveillance systems, as similar designs of surveillance systems exist across the region. Although sudden surveillance disruption is possible at a country or regional level, it is unlikely to occur in all countries simultaneously. Retrospective modelling with epidemiological, immunological and entomological information is needed. Host or immunological factors may have influenced the decline in dengue cases at the population level through immunity; however, herd protection requires additional evidence. Uncertainty remains regarding the effect on the outcome of sequential infections of different dengue virus (DENV) types and Zika virus (ZIKV), and vice versa. Future studies were recommended that examine the epidemiological effect of prior DENV infection on Zika incidence and severity, the epidemiological effect of prior Zika virus infection on dengue incidence and severity, immune correlates based on new-generation ELISA assays, and impact of prior DENV/other arbovirus infection on ZIKV immune response in relation to number of infections and the duration of antibodies in relation to interval of protection. Follow-up studies should also investigate whether increased vector control intensification activities contributed to the decline in transmission of one or more of these arboviruses. Additionally, proposed studies should focus on the potential role of vector competence when simultaneously exposed to various arboviruses, and on entomological surveillance and its impact on circulating vector species, with a goal of applying specific measures that mitigate seasonal occurrence or outbreaks.Multifactorial events may have accounted for the decline in dengue seen in 2017. Differing elements might explain the reduction in dengue including elements of immunity, increased vector control, and even vector and\or viruses changes or adaptations. Most of the results of this expert consensus group meeting are hypothetical and based on limited evidence. Further studies are needed.Depuis les années 1980, l'incidence de la dengue a été multipliée par 30. Cependant, en 2017, il y a eu une réduction notable du nombre de cas d'incidence de dengue rapportés dans les Amériques. Nous voulions fournir des explications plausibles à la baisse en 2017. MÉTHODES: Un groupe d'experts constitué de représentants d'institutions scientifiques et académiques, d'officiels des Ministères de la Santé d'Amérique Latine et de membres du personnel de l’OPS/OMS s'est réuni en octobre 2017 pour proposer et évaluer des hypothèses. RÉSULTATS: En 2017, il y a eu une baisse généralisée de l'incidence, de la sévérité et du nombre de décès dus à la dengue dans les Amériques, accompagnée d'une réduction des cas rapportés d'infections par le virus Zika et par le virus du chikungunya, sans modification dans la répartition entre les groupes d’âge affectés. Il a été déterminé que ce déclin était peu probablement dû aux changements dans les systèmes de surveillance épidémiologique, étant donné que des systèmes de surveillance similaires existaient dans toute la région. Bien que des perturbations soudaines dans la surveillance soient possibles au niveau national ou régional, il est peu probable que cela se produise simultanément dans tous les pays. Une modélisation rétrospective avec des informations épidémiologiques, immunologiques et entomologiques est nécessaire. Des facteurs liés à l'hôte ou immunologiques peuvent avoir influencé le déclin des cas de dengue au niveau de la population par le biais de l'immunité; cependant, l’évidence d'une protection conférée par l'effet du troupeau nécessite des données supplémentaires. Une incertitude subsiste quant à l'effet sur le résultat des infections séquentielles de différents types du virus de la dengue (DENV) et du virus Zika (ZIKV), et vice-versa. Les études à venir devraient examiner (1) l'effet épidémiologique d'une infection antérieure par le DENV sur l'incidence et la sévérité du virus Zika, (2) l'effet épidémiologique d'une infection antérieure par le virus Zika sur l'incidence et la sévérité de la dengue, (3) les corrélats immunitaires basés sur des tests ELISA de nouvelle génération, (4) l’ impact d'une infection antérieure à DENV/autres arbovirus sur la réponse immunitaire au ZIKV en fonction du nombre d'infections et de la durée des anticorps en fonction de l'intervalle de protection, (5) si des activités d'intensification de la lutte antivectorielle ont contribué à la diminution de la transmission d'un ou plusieurs de ces arbovirus, (6) le rôle potentiel de la compétence vectorielle lorsqu'ils sont exposés simultanément à différents arbovirus, (7) la surveillance entomologique et son impact sur la circulation d'espèces de vecteurs, dans le but d'appliquer des mesures spécifiques qui réduisent l'occurrence saisonnière d’épidémies.Des événements multifactoriels pourraient expliquer le déclin observé de la dengue en 2017. La plupart des résultats de cette réunion du groupe de consensus d'experts sont hypothétiques, reposent sur des données limitées et requièrent des investigations supplémentaires.

In 2009, the Robert Koch Institute (RKI) and the 16 German federal state public health authorities (PHAs) established a weekly epidemiological teleconference (EpiLag) to discuss infectious disease (ID) events and foster horizontal and vertical information exchange. We present the procedure, discussed ID topics and evaluation results of EpiLag after 10 years. We analysed attendance, duration of EpiLag and the frequency of reported events. Participants (RKI and state PHA) were surveyed regarding their satisfaction with logistics, contents and usefulness of EpiLag (Likert scales). Between 2009 and 2018, RKI hosted 484 EpiLag conferences with a mean duration of 25 min (range: 4–60) and high participation (range: 9–16; mean: 15 PHAs). Overall, 2975 ID events (39% international, 9% national and 52% subnational) were presented (mean: 6.1 per EpiLag), most frequently on measles (18%), salmonellosis (8%) and influenza (5%). All responding participants (14/16 PHAs and 9/9 at RKI) were satisfied with the EpiLag's organization and minutes and deemed EpiLag useful for an overview and information distribution on ID events relevant to Germany. EpiLag is time efficient, easily applicable and useful for a low-threshold event communication. It supports PHAs in crises and strengthens the network of surveillance stakeholders. We recommend its implementation to other countries or sectors.

During the coronavirus disease 2019 (COVID-19) pandemic, many countries opted for strict public health measures, including closing schools. After some time, they have started relaxing some of those restrictions. To avoid overwhelming health systems, predictions for the number of new COVID-19 cases need to be considered when choosing a school reopening strategy. Using a computer simulation based on a stochastic compartmental model that includes a heterogeneous and dynamic network, we analyse different strategies to reopen schools in the São Paulo Metropolitan Area, including one similar to the official reopening plan. Our model allows us to describe different types of relations between people, each type with a different infectiousness. Based on our simulations and model assumptions, our results indicate that reopening schools with all students at once has a big impact on the number of new COVID-19 cases, which could cause a collapse of the health system. On the other hand, our results also show that a controlled school reopening could possibly avoid the collapse of the health system, depending on how people follow sanitary measures. We estimate that postponing the schools' return date for after a vaccine becomes available may save tens of thousands of lives just in the São Paulo Metropolitan Area compared to a controlled reopening considering a worst-case scenario. We also discuss our model constraints and the uncertainty of its parameters.

Highlights • Vaccine preventable diseases continue to impact human health. • Web-based geographic temporal visualizations of large datasets were developed. • Data on rotavirus vaccination uptake and related medical visits was used as an example. • Visualizations show vaccine effectiveness by geographic levels and over time. • Project informs strategies to monitor the impact of new vaccines on SARS-CoV-2., Background Infectious diseases continue to cause significant impact on human health. Vaccines are instrumental in preventing infectious diseases and mitigating pandemics and epidemics. SARS-CoV-2 is the most recent example of an urgent pandemic that requires the development of vaccines. This study combined real-world data and geospatial visualization techniques to demonstrate methods to monitor and communicate the uptake and impact of existing and new vaccines. Methods Observational data of existing pediatric rotavirus vaccines were used as an example. A large US national insurance claims database was accessed to build an analytic dataset for a 20-year period (1996–2017). For each week and multiple geographic scales, animated spatial and non-spatial visualization techniques were applied to demonstrate changes in seasonal rotavirus epidemic curves and population-based disease rates before, during, and after vaccine introduction in 2006. The geographic scales included national, state, county and zip code tabulation areas. An online web-based digital atlas was built to display either continuous or snapshot visualizations of disease patterns, vaccine uptake, and improved health outcomes after vaccination (http://www.mapvaccines.com). Results Over 17 million zip code-weeks of data were available for analysis. The animations show geospatial patterns of rotavirus-related medical encounter rates peaking every year from November – February prior to vaccine availability in 2006. Visualizations showed increasing vaccination coverage rates at all geographic scales over time. Declines in medical encounter rates accelerated as vaccination coverage rapidly increased after 2010. The data maps also identified geographic hotspots with low vaccination rates and persistent disease rates. Conclusion This project developed novel web-based methods to communicate location and time-based vaccine uptake and the related reduction in medical visits due to viral infection. Future applications of the visualization could be used by health agencies to monitor known or novel disease patterns over time in conjunction with close assessment of current and future vaccine utilization.

Severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2) led to a significant disease burden and disruptions in health systems. We describe the epidemiology and transmission characteristics of early coronavirus disease 2019 (COVID-19) cases in Bavaria, Germany. Cases were reverse transcription polymerase chain reaction (RT-PCR)-confirmed SARS-CoV-2 infections, reported from 20 January−19 March 2020. The incubation period was estimated using travel history and date of symptom onset. To estimate the serial interval, we identified pairs of index and secondary cases. By 19 March, 3546 cases were reported. A large proportion was exposed abroad (38%), causing further local transmission. Median incubation period of 256 cases with exposure abroad was 3.8 days (95%CI: 3.5–4.2). For 95% of infected individuals, symptom onset occurred within 10.3 days (95%CI: 9.1–11.8) after exposure. The median serial interval, using 53 pairs, was 3.5 days (95%CI: 3.0–4.2; mean: 3.9, s.d.: 2.2). Travellers returning to Germany had an important influence on the spread of SARS-CoV-2 infections in Bavaria in early 2020. Especially in times of low incidence, public health agencies should identify holiday destinations, and areas with ongoing local transmission, to monitor potential importation of SARS-CoV-2 infections. Travellers returning from areas with ongoing community transmission should be advised to quarantine to prevent re-introductions of COVID-19.

In April 2018, Public Health England was notified of cases of Shigella sonnei who had eaten food from three different catering outlets in England. The outbreaks were initially investigated as separate events, but whole-genome sequencing (WGS) showed they were caused by the same strain. The investigation included analyses of epidemiological data, the food chain and microbiological examination of food samples. WGS was used to determine the phylogenetic relatedness and antimicrobial resistance profile of the outbreak strain. Ultimately, 33 cases were linked to this outbreak; the majority had eaten food from seven outlets specialising in Indian or Middle Eastern cuisine. Five outlets were linked to two or more cases, all of which used fresh coriander although a shared supplier was not identified. An investigation at one of the venues recorded that 86% of cases reported eating dishes with coriander as an ingredient or garnish. Four cases were admitted to hospital and one had evidence of treatment failure with ciprofloxacin. Phylogenetic analysis showed that the outbreak strain was part of a wider multidrug-resistant clade associated with travel to Pakistan. Poor hygiene practices during cultivation, distribution or preparation of fresh produce are likely contributing factors.

This study aims to locate the knots of cumulative coronavirus disease 2019 (COVID-19) case number during the first-level response to public health emergency in the provinces of China except Hubei. The provinces were grouped into three regions, namely eastern, central and western provinces, and the trends between adjacent knots were compared among the three regions. COVID-19 case number, migration scale index, Baidu index, demographic, economic and public health resource data were collected from 22 Chinese provinces from 19 January 2020 to 12 March 2020. Spline regression was applied to the data of all included, eastern, central and western provinces. The research period was divided into three stages by two knots. The first stage (from 19 January to around 25 January) was similar among three regions. However, in the second stage, growth of COVID-19 case number was flatter and lasted longer in western provinces (from 25 January to 18 February) than in eastern and central provinces (from 26 February to around 11 February). In the third stage, the growth of COVID-19 case number slowed down in all the three regions. Included covariates were different among the three regions. Overall, spline regression with covariates showed the different change patterns in eastern, central and western provinces, which provided a better insight into regional characteristics of COVID-19 pandemic.

The Republic of Ireland (ROI) currently reports the highest incidence rates of Shiga-toxin producing Escherichia coli (STEC) enteritis and cryptosporidiosis in Europe, with the spatial distribution of both infections exhibiting a clear urban/rural divide. To date, no investigation of the role of socio-demographic profile on the incidence of either infection in the ROI has been undertaken. The current study employed bivariate analyses and Random Forest classification to identify associations between individual components of a national deprivation index and spatially aggregated cases of STEC enteritis and cryptosporidiosis. Classification accuracies ranged from 78.2% (STEC, urban) to 90.6% (cryptosporidiosis, rural). STEC incidence was (negatively) associated with a mean number of persons per room and percentage of local authority housing in both urban and rural areas, addition to lower levels of education in rural areas, while lower unemployment rates were associated with both infections, irrespective of settlement type. Lower levels of third-level education were associated with cryptosporidiosis in rural areas only. This study highlights settlement-specific disparities with respect to education, unemployment and household composition, associated with the incidence of enteric infection. Study findings may be employed for improved risk communication and surveillance to safeguard public health across socio-demographic profiles.

Estimating the case fatality ratio (CFR) for COVID-19 is an important aspect of public health. However, calculating CFR accurately is problematic early in a novel disease outbreak, due to uncertainties regarding the time course of disease and difficulties in diagnosis and reporting of cases. In this work, we present a simple method for calculating the case fatality ratio using only public case and death data over time by exploiting the correspondence between the time distributions of cases and deaths. The time-shifted distribution (TSD) analysis generates two parameters of interest: the delay time between reporting of cases and deaths and the case fatality ratio. These parameters converge reliably over time once the exponential growth phase has finished. Analysis is performed for early COVID-19 outbreaks in many countries, and we discuss corrections to CFR values using excess-death and seroprevalence data to estimate the infection fatality ratio (IFR). While CFR values range from 0.2-20% in different countries, estimates for IFR are mostly around 0.5-0.8% for countries that experienced moderate outbreaks and 1-3% for severe outbreaks. The simplicity and transparency of TSD analysis enhance its usefulness in characterizing a new disease as well as the state of the health and reporting systems.

In November 2017, eight confirmed measles cases were reported to Public Health England from a hospital in the West Midlands. A multidisciplinary Incident Management Team (IMT) was established to determine the extent of the problem and coordinate an outbreak response. Between 1 November 2017 and 4 June 2018, a total of 116 confirmed and 21 likely measles cases were linked to this outbreak; just under half (43%) were aged over 15 years of age. Fifty-five of the confirmed cases were hospitalised (48%) and no deaths were reported. At the start of the outbreak, cases were mostly individuals of Romanian origin; the outbreak subsequently spread to the wider population. Over the 8-month response, the IMT conducted the following control measures: extensive contact tracing, immediate provision of post-exposure prophylaxis, community engagement amongst specific high-risk groups, MMR awareness raising including catch-up campaigns and enhanced vaccination services at selected GP surgeries. Key challenges to the effective control measures included language difficulties limiting community engagement; delays in diagnosis, notification and appropriate isolation of cases; limited resources for contact tracing across multiple high-risk settings (including GPs and hospitals) and lack of timely data on vaccine coverage in sub-groups of the population to guide public health action.

The coronavirus disease 2019 (COVID-19) pandemic is currently the most critical challenge in public health. An understanding of the factors that affect severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2) infection will help fight the COVID-19 pandemic. This study sought to investigate the association between SARS-CoV-2 infection and blood type distribution. The big data provided by the World Health Organization (WHO) and Johns Hopkins University were used to assess the dynamics of the COVID-19 epidemic. The infection data in the early phase of the pandemic from six countries in each of six geographic zones divided according to the WHO were used, representing approximately 5.4 billion people around the globe. We calculated the infection growth factor, doubling times of infection and death cases, reproductive number and infection and death cases in relation to the blood type distribution. The growth factor of infection and death cases significantly and positively correlated with the proportion of the population with blood type A and negatively correlated with the proportion of the population with blood type B. Compared with the lower blood type A population (

Successive waves of COVID-19 transmission have led to exponential increases in new infections globally. In this study, we have applied a decision-making tool to assess the risk of continuing transmission to inform decisions on tailored public health and social measures (PHSM) using data on cases and deaths reported by Member States to the WHO Regional Office for Africa as of 31 December 2020. Transmission classification and health system capacity were used to assess the risk level of each country to guide implementation and adjustments to PHSM. Two countries out of 46 assessed met the criteria for sporadic transmission, one for clusters of cases, and 43 (93.5%) for community transmission (CT) including three with uncontrolled disease incidence (Eswatini, Namibia and South Africa). Health system response's capacities were assessed as adequate in two countries (4.3%), moderate in 13 countries (28.3%) and limited in 31 countries (64.4%). The risk level, calculated as a combination of transmission classification and health system response's capacities, was assessed at level 0 in one country (2.1%), level 1 in two countries (4.3%), level 2 in 11 countries (23.9%) and level 3 in 32 (69.6%) countries. The scale of severity ranged from 0 to 4, with 0 the lowest. CT coupled with limited response capacity resulted in a level 3 risk assessment in most countries. Countries at level 3 should be considered as priority focus for additional assistance, in order to prevent the risk rising to level 4, which may necessitate enforcing hard and costly lockdown measures. The large number of countries at level 3 indicates the need for an effective risk management system to be used as a basis for adjusting PHSM at national and sub-national levels.

The objective of this study was to analyse the dynamics of spatial dispersion of the coronavirus disease 2019 (COVID-19) in Brazil by correlating them to socioeconomic indicators. This is an ecological study of COVID-19 cases and deaths between 26 February and 31 July 2020. All Brazilian counties were used as units of analysis. The incidence, mortality, Bayesian incidence and mortality rates, global and local Moran indices were calculated. A geographic weighted regression analysis was conducted to assess the relationship between incidence and mortality due to COVID-19 and socioeconomic indicators (independent variables). There were confirmed 2 662 485 cases of COVID-19 reported in Brazil from February to July 2020 with higher rates of incidence in the north and northeast. The Moran global index of incidence rate (0.50, P = 0.01) and mortality (0.45 with P = 0.01) indicate a positive spatial autocorrelation with high standards in the north, northeast and in the largest urban centres between cities in the southeast region. In the same period, there were 92 475 deaths from COVID-19, with higher mortality rates in the northern states of Brazil, mainly Amazonas, Pará and Amapá. The results show that there is a geospatial correlation of COVID-19 in large urban centres and regions with the lowest human development index in the country. In the geographic weighted regression, it was possible to identify that the percentage of people living in residences with density higher than 2 per dormitory, the municipality human development index (MHDI) and the social vulnerability index were the indicators that most contributed to explaining incidence, social development index and the municipality human development index contributed the most to the mortality model. We hope that the findings will contribute to reorienting public health responses to combat COVID-19 in Brazil, the new epicentre of the disease in South America, as well as in other countries that have similar epidemiological and health characteristics to those in Brazil.

The global outbreak of coronavirus disease 2019 (COVID-19) is greatly threatening the public health in the world. We reconstructed global transmissions and potential demographic expansions of severe acute respiratory syndrome coronavirus 2 based on genomic information. We found that intercontinental transmissions were rare in January and early February but drastically increased since late February. After world-wide implements of travel restrictions, the transmission frequencies decreased to a low level in April. We identified a total of 88 potential demographic expansions over the world based on the star-radiative networks and 75 of them were found in Europe and North America. The expansion numbers peaked in March and quickly dropped since April. These findings are highly concordant with epidemic reports and modelling results and highlight the significance of quarantine validity on the global spread of COVID-19. Our analyses indicate that the travel restrictions and social distancing measures are effective in containing the spread of COVID-19.

Amplifying the testing capacity and making better use of testing resources is a crucial measure when fighting any pandemic. A pooled testing strategy for SARS-CoV-2 has theoretically been shown to increase the testing capacity of a country, especially when applied in low prevalence settings. Experimental studies have shown that the sensitivity of reverse transcription-polymerase chain reaction is not affected when implemented in small groups. Previous models estimated the optimum group size as a function of the historical prevalence; however, this implies a homogeneous distribution of the disease within the population. This study aimed to explore whether separating individuals by age groups when pooling samples results in any further savings on test kits or affects the optimum group size estimation compared to Dorfman's pooling, based on historical prevalence. For this evaluation, age groups of interest were defined as 0–19 years, 20–59 years and over 60 years old. Generalisation of Dorfman's pooling was performed by adding statistical weight to the age groups based on the number of confirmed cases and tests performed in the segment. The findings showed that when the pooling samples are based on age groups, there is a decrease in the number of tests per subject needed to diagnose one subject. Although this decrease is minuscule, it might account for considerable savings when applied on a large scale. In addition, the savings are considerably higher in settings where there is a high standard deviation among the positivity rate of the age segments of the general population.

We investigated a large gastroenteritis outbreak that occurred in Northern Greece in 2019. A case was defined as anyone presenting with diarrhoea and/or vomiting from 24 January 2019 to 04 February 2019. We conducted a case-control study (CCS) using random selection of participants >16 years of age, residents of town X, who visited the health care centre between 25 and 28 January 2019. Moreover, we conducted a retrospective cohort study (CS) at the four elementary schools of the town. We collected clinical and water samples and the water supply system was inspected. In total, we recorded 638 cases (53% female; median age was 44 years (range 0–93)). Forty-eight cases and 52 controls participated in the CCS and 236 students in the CS. Both CCS and CS indicated tap water as the most likely source (OR 10, 95% CI 2.09–93.4, explaining 95.7% of cases; RR = 2.22, 95% CI 1.42–3.46, respectively). More than one pathogen was detected from stool samples of 6 of the 11 cases tested (norovirus, Campylobacter jejuni, Enterohemorrhagic E. coli (EHEC) and Enteropathogenic E. coli (EPEC)). Water samples, collected after ad-hoc chlorination, tested negative. Technical failures of the water tanks' status were identified. Our results suggested a waterborne outbreak. We recommended regular monitoring of the water supply system and immediate repair of technical failures.

The outbreak of coronavirus disease-2019 (COVID-19) impacts public health dramatically around the world. The demographic characteristics, exposure history, dates of illness onset and dates of confirmed diagnosis were collected from the data of 24 family clusters from Beijing. The characteristics of the cases and the estimated key epidemiologic time-to-event distributions were described. The basic reproductive number (R0) was calculated. Among 89 confirmed COVID-19 patients from 24 family clusters, the median age was 38.0 years and 43.8% were male. The median of incubation period was 5.08 days (95% confidence interval (CI) 4.17–6.21). The median of serial interval was 6.00 days (95% CI 5.00–7.00). The basic reproductive number (R0) was 2.06 (95% CI 2.02–2.08). The median of onset-to-care-seeking days and the median of onset-to-hospital admission days were significantly reduced after 23 January 2020, which implied the enhanced public health awareness among families. With epidemic containment measures in place, the results can inform health authorities about possible extent of epidemic transmission within families. Furthermore, following initiation of interventions, public health measures are not only important for curbing the epidemic spread at the community level but also improve health seeking behaviour at the individual level.

Background COVID-19 emerged as a major public health outbreak in late 2019. Malaysia reported its first imported case on 25th January 2020, and adopted a policy of extensive contact tracing and hospitalising of all cases. We describe the clinical characteristics of COVID-19 cases nationwide and determine the risk factors associated with disease severity. Method Clinical records of all RT-PCR confirmed COVID-19 cases aged ≥12 years admitted to 18 designated hospitals in Malaysia between 1st February and 30th May 2020 with complete outcomes were retrieved. Epidemiological history, co-morbidities, clinical features, investigations, management and complications were captured using REDCap database. Variables were compared between mild and severe diseases. Univariate and multivariate regression were used to identify determinants for disease severity. Findings The sample comprised of 5889 cases (median age 34 years, male 71.7%). Majority were mild (92%), and 3.3% required intensive care, with 80% admitted within the first five days. Older age (≥51 years), underlying chronic kidney disease and chronic pulmonary disease, fever, cough, diarrhoea, breathlessness, tachypnoea, abnormal chest radiographs and high serum CRP (≥5 mg/dL) on admission were significant determinants for severity (p Interpretations Lower case fatality rate was possibly contributed by young cases with mild diseases and early hospitalisation. Abnormal chest radiographic findings in elderly with tachypnoea require close monitoring in the first five days to detect early deterioration.