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Summary Objective Although elimination of leprosy was achieved in Nepal at national level in 2009, around 3000 new cases are still detected every year and 5% of these cases have Grade 2 disability (G2D). This study aims to describe the geographical distribution of leprosy new case detection (NCD) and G2D from 2010 to 2021 in two leprosy endemic provinces in Nepal. Methods We collected the geolocations and leprosy-related data of patients registered from 2010 to 2021 in Provinces 1 and 7. The geographical distribution of NCD and G2D was analysed in Quantum Geographic Information Systems (QGIS) at district, municipality and ward level, and we calculated the trends in Eye Hand Foot (EHF) impairment scores among cases with disabilities. Results From 2010 to 2021, a decrease in NCD and G2D cases was identified in Province 1, and an increase in NCD and G2D cases in Province 7. Geographical variations were visible between wards within highly endemic districts in both provinces. The mean EHF score in cases with disability increased from 1.7 in 2017 to 2.5 in 2020 in Province 1 and fluctuated between 2.3 and 4.5 in Province 7. Conclusions This study shows that the leprosy problem is still current in Nepal. Geographic variations in case detection and disability indicators are seen best when mapping at ward level. Leprosy programme managers can use the maps to develop long-term strategies at district, municipality or ward level that include intensified active case finding, preventive treatment and disability services, while considering costs and efficient use of resources.

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.

Background Due to spatial heterogeneity in onchocerciasis transmission, the duration of ivermectin mass drug administration (MDA) required for eliminating onchocerciasis will vary within endemic areas and the occurrence of transmission “hotspots” is inevitable. The geographical scale at which stop-MDA decisions are made will be a key driver in how rapidly national programs can scale down active intervention upon achieving the epidemiological targets for elimination. Methods We used 2 onchocerciasis models (EPIONCHO-IBM and ONCHOSIM) to predict the likelihood of achieving elimination by 2030 in Africa, accounting for variation in preintervention endemicity levels and histories of ivermectin treatment. We explore how decision making at contrasting geographical scales (community vs larger scale “project”) changes projections on populations still requiring MDA or transitioning to post-treatment surveillance. Results The total population considered grows from 118 million people in 2020 to 136 million in 2030. If stop-MDA decisions are made at project level, the number of people requiring treatment declines from 69–118 million in 2020 to 59–118 million in 2030. If stop-MDA decisions are made at community level, the numbers decline from 23–81 million in 2020 to 15–63 million in 2030. The lower estimates in these prediction intervals are based on ONCHOSIM, the upper limits on EPIONCHO-IBM. Conclusions The geographical scale at which stop-MDA decisions are made strongly determines how rapidly national onchocerciasis programs can scale down MDA programs. Stopping in portions of project areas or transmission zones would free up human and economic resources.

Background Mass drug administration (MDA) with ivermectin is the main strategy for onchocerciasis elimination. Ivermectin is generally safe, but is associated with serious adverse events in individuals with high Loa loa microfilarial densities (MFD). Therefore, ivermectin MDA is not recommended in areas where onchocerciasis is hypo-endemic and L loa is co-endemic. To eliminate onchocerciasis in those areas, a test-and-not-treat (TaNT) strategy has been proposed. We investigated whether onchocerciasis elimination can be achieved using TaNT and the required duration. Methods We used the individual-based model ONCHOSIM to predict the impact of TaNT on onchocerciasis microfilarial (mf) prevalence. We simulated precontrol mf prevalence levels from 2% to 40%. The impact of TaNT was simulated under varying levels of participation, systematic nonparticipation, and exclusion from ivermectin resulting from high L loa MFD. For each scenario, we assessed the time to elimination, defined as bringing onchocerciasis mf prevalence below 1.4%. Results In areas with 30% to 40% precontrol mf prevalence, the model predicted that it would take between 14 and 16 years to bring the mf prevalence below 1.4% using conventional MDA, assuming 65% participation. TaNT would increase the time to elimination by up to 1.5 years, depending on the level of systematic nonparticipation and the exclusion rate. At lower exclusion rates (≤2.5%), the delay would be less than 6 months. Conclusions Our model predicts that onchocerciasis can be eliminated using TaNT in L loa co-endemic areas. The required treatment duration using TaNT would be only slightly longer than in areas with conventional MDA, provided that participation is good., Our model predicts that onchocerciasis can be eliminated using test-and-not-treat (TaNT) in L loa co-endemic areas. The required treatment duration using TaNT would be only slightly longer than in areas with conventional mass drug administration, provided that participation is good.

Background Leprosy is known to be unevenly distributed between and within countries. High risk areas or ‘hotspots’ are potential targets for preventive interventions, but the underlying epidemiologic mechanisms that enable hotspots to emerge, are not yet fully understood. In this study, we identified and characterized leprosy hotspots in Bangladesh, a country with one of the highest leprosy endemicity levels globally. Methods We used data from four high-endemic districts in northwest Bangladesh including 20 623 registered cases between January 2000 and April 2019 (among ~ 7 million population). Incidences per union (smallest administrative unit) were calculated using geospatial population density estimates. A geospatial Poisson model was used to detect incidence hotspots over three (overlapping) 10-year timeframes: 2000–2009, 2005–2014 and 2010–2019. Ordinal regression models were used to assess whether patient characteristics were significantly different for cases outside hotspots, as compared to cases within weak (i.e., relative risk (RR) of one to two), medium (i.e., RR of two to three), and strong (i.e., RR higher than three) hotspots. Results New case detection rates dropped from 44/100 000 in 2000 to 10/100 000 in 2019. Statistically significant hotspots were identified during all timeframes and were often located at areas with high population densities. The RR for leprosy was up to 12 times higher for inhabitants of hotspots than for people living outside hotspots. Within strong hotspots (1930 cases among less than 1% of the population), significantly more child cases (i.e., below 15 years of age) were detected, indicating recent transmission. Cases in hotspots were not significantly more likely to be detected actively. Conclusions Leprosy showed a heterogeneous distribution with clear hotspots in northwest Bangladesh throughout a 20-year period of decreasing incidence. Findings confirm that leprosy hotspots represent areas of higher transmission activity and are not solely the result of active case finding strategies.

Background In line with movement restrictions and physical distancing essential for the control of the COVID-19 pandemic, WHO recommended postponement of all neglected tropical disease (NTD) control activities that involve community-based surveys, active case finding, and mass drug administration in April, 2020. Following revised guidance later in 2020, and after interruptions to NTD programmes of varying lengths, NTD programmes gradually restarted in the context of an ongoing pandemic. However, ongoing challenges and service gaps have been reported. This study aimed to evaluate the potential effect of the programmatic interruptions and strategies to mitigate this effect. Methods For seven NTDs, namely soil-transmitted helminths, schistosomiasis, lymphatic filariasis, onchocerciasis, trachoma, visceral leishmaniasis, and human African trypanosomiasis, we used mathematical transmission models to simulate the effect of programme interruptions on the dynamics of each of these diseases in different endemic settings. We also explored the potential benefit of implementing mitigation strategies, primarily in terms of minimising the delays to control targets. Findings We show that the effect of the COVID-19-induced interruption in terms of delay to achieving elimination goals might in some cases be much longer than the duration of the interruption. For schistosomiasis, onchocerciasis, trachoma, and visceral leishmaniasis, a mean delay of 2–3 years for a 1-year interruption is predicted in areas of highest prevalence. We also show that these delays can largely be mitigated by measures such as additional mass drug administration or enhanced case-finding. Interpretation The COVID-19 pandemic has brought infectious disease control to the forefront of global consciousness. It is essential that the NTDs, so long neglected in terms of research and financial support, are not overlooked, and remain a priority in health service planning and funding. Funding Bill & Melinda Gates Foundation, Medical Research Council, and the UK Foreign, Commonwealth & Development Office.

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.

Due to the COVID-19 pandemic, many key neglected tropical disease (NTD) activities have been postponed. This hindrance comes at a time when the NTDs are progressing towards their ambitious goals for 2030. Mathematical modelling on several NTDs, namely gambiense sleeping sickness, lymphatic filariasis, onchocerciasis, schistosomiasis, soil-transmitted helminthiases (STH), trachoma, and visceral leishmaniasis, shows that the impact of this disruption will vary across the diseases. Programs face a risk of resurgence, which will be fastest in high-transmission areas. Furthermore, of the mass drug administration diseases, schistosomiasis, STH, and trachoma are likely to encounter faster resurgence. The case-finding diseases (gambiense sleeping sickness and visceral leishmaniasis) are likely to have fewer cases being detected but may face an increasing underlying rate of new infections. However, once programs are able to resume, there are ways to mitigate the impact and accelerate progress towards the 2030 goals., The COVID-19 pandemic has disrupted neglected tropical disease programs. Modelling shows the impact of this will vary across diseases. Once interventions are reintroduced, there are opportunities for mitigating the delay and accelerating progress towards the 2030 goals.

Background The Leprosy Post-Exposure Prophylaxis (LPEP) program explored the feasibility and impact of contact tracing and the provision of single dose rifampicin (SDR) to eligible contacts of newly diagnosed leprosy patients in Brazil, India, Indonesia, Myanmar, Nepal, Sri Lanka and Tanzania. As the impact of the programme is difficult to establish in the short term, we apply mathematical modelling to predict its long-term impact on the leprosy incidence. Methodology The individual-based model SIMCOLEP was calibrated and validated to the historic leprosy incidence data in the study areas. For each area, we assessed two scenarios: 1) continuation of existing routine activities as in 2014; and 2) routine activities combined with LPEP starting in 2015. The number of contacts per index patient screened varied from 1 to 36 between areas. Projections were made until 2040. Principal findings In all areas, the LPEP program increased the number of detected cases in the first year(s) of the programme as compared to the routine programme, followed by a faster reduction afterwards with increasing benefit over time. LPEP could accelerate the reduction of the leprosy incidence by up to six years as compared to the routine programme. The impact of LPEP varied by area due to differences in the number of contacts per index patient included and differences in leprosy epidemiology and routine control programme. Conclusions The LPEP program contributes significantly to the reduction of the leprosy incidence and could potentially accelerate the interruption of transmission. It would be advisable to include contact tracing/screening and SDR in routine leprosy programmes., Author summary The Leprosy Post-Exposure Prophylaxis (LPEP) program explored the feasibility and impact of contact tracing and the provision of SDR to eligible contacts of newly diagnosed leprosy patients in states or districts of Brazil, India, Indonesia, Myanmar, Nepal, Sri Lanka and Tanzania. This study investigated the long-term impact of the LPEP program on the leprosy new case detection rate (NCDR). Our results show that LPEP could reduce the NCDR beyond the impact of the routine leprosy control programme and that many new cases could be prevented. The benefit of LPEP increases gradually over time. LPEP could accelerate the time of reaching predicted NCDR levels of 2040 under routine program by up to six years. Furthermore, we highlighted how the impact varies between countries due to differences in the number of contacts per index patient screened and differences in leprosy epidemiology and national control programme. Generally, including both household contacts and neighbours (> 20 contacts per index patient) would yield the highest impact.

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.

Background Mass drug administration (MDA) of ivermectin for onchocerciasis has been disrupted by the coronavirus disease 2019 (COVID-19) pandemic. Mathematical modelling can help predict how missed/delayed MDA will affect short-term epidemiological trends and elimination prospects by 2030. Methods Two onchocerciasis transmission models (EPIONCHO-IBM and ONCHOSIM) are used to simulate microfilarial prevalence trends, elimination probabilities and age profiles of Onchocerca volvulus microfilarial prevalence and intensity for different treatment histories and transmission settings, assuming no interruption, a 1-y (2020) interruption or a 2-y (2020–2021) interruption. Biannual MDA or increased coverage upon MDA resumption are investigated as remedial strategies. Results Programmes with shorter MDA histories and settings with high pre-intervention endemicity will be the most affected. Biannual MDA is more effective than increasing coverage for mitigating COVID-19’s impact on MDA. Programmes that had already switched to biannual MDA should be minimally affected. In high-transmission settings with short treatment history, a 2-y interruption could lead to increased microfilarial load in children (EPIONCHO-IBM) and adults (ONCHOSIM). Conclusions Programmes with shorter (annual MDA) treatment histories should be prioritised for remedial biannual MDA. Increases in microfilarial load could have short- and long-term morbidity and mortality repercussions. These results can guide decision-making to mitigate the impact of COVID-19 on onchocerciasis elimination.

India has the highest burden of leprosy in the world. Following a recent WHO guideline, the Indian National Leprosy Programme is introducing post-exposure prophylaxis with single-dose rifampicin (SDR-PEP) in all high-endemic districts of the country. The aim of this study is to estimate the long-term cost-effectiveness of SDR-PEP in different leprosy disability burden situations. We used a stochastic individual-based model (SIMCOLEP) to simulate the leprosy new case detection rate trend and the impact of implementing contact screening and SDR-PEP from 2016 to 2040 (25 years) in the Union Territory of Dadra Nagar Haveli (DNH) in India. Effects of the intervention were expressed as disability adjusted life years (DALY) averted under three assumption of disability prevention: 1) all grade 1 disability (G1D) cases prevented; 2) G1D cases prevented in PB cases only; 3) no disability prevented. Costs were US$ 2.9 per contact. Costs and effects were discounted at 3%. The incremental cost per DALY averted by SDR-PEP was US$ 210, US$ 447, and US$ 5,673 in the 25th year under assumption 1, 2, and 3, respectively. If prevention of G1D was assumed, the probability of cost-effectiveness was 1.0 at the threshold of US$ 2,000, which is equivalent to the GDP per capita of India. The probability of cost-effectiveness was 0.6, if no disability prevention was assumed. The cost per new leprosy case averted was US$ 2,873. Contact listing, screening and the provision of SDR-PEP is a cost-effective strategy in leprosy control in both the short (5 years) and long term (25 years). The cost-effectiveness depends on the extent to which disability can be prevented. As the intervention becomes increasingly cost-effective in the long term, we recommend a long-term commitment for its implementation., Author summary Leprosy is an infectious disease caused by the Mycobacterium leprae and is one of the major causes of preventable disability in low- and middle-income countries. Disabled people face lifelong socioeconomic challenges and are often excluded from society. It brings people affected by leprosy in a vicious cycle of poverty and disability. This cycle needs to be curbed through scientific evidence on health economic aspects of leprosy. Unfortunately, there is not much literature available on cost or cost-effectiveness of leprosy prevention. New prevention methods such as post-exposure chemoprophylaxis are now available, providing opportunity to collect up-to-date health economic evidence to support health policy and planning. Here, we present a cost-effectiveness study of contact screening in combination of post-exposure prophylaxis with single-dose rifampicin in the Union Territory of Dadra Nagar Haveli in India. We compare the intervention with the continuation of the routine leprosy control programme. As leprosy is moving towards elimination, evidence from this study will contribute to an investment case for leprosy elimination.

Summary Background Innovative approaches are required for leprosy control to reduce cases and curb transmission of Mycobacterium leprae. Early case detection, contact screening, and chemoprophylaxis are the most promising tools. We aimed to generate evidence on the feasibility of integrating contact tracing and administration of single-dose rifampicin (SDR) into routine leprosy control activities. Methods The leprosy post-exposure prophylaxis (LPEP) programme was an international, multicentre feasibility study implemented within the leprosy control programmes of Brazil, India, Indonesia, Myanmar, Nepal, Sri Lanka, and Tanzania. LPEP explored the feasibility of combining three key interventions: systematically tracing contacts of individuals newly diagnosed with leprosy; screening the traced contacts for leprosy; and administering SDR to eligible contacts. Outcomes were assessed in terms of number of contacts traced, screened, and SDR administration rates. Findings Between Jan 1, 2015, and Aug 1, 2019, LPEP enrolled 9170 index patients and listed 179 769 contacts, of whom 174 782 (97·2%) were successfully traced and screened. Of those screened, 22 854 (13·1%) were excluded from SDR mainly because of health reasons and age. Among those excluded, 810 were confirmed as new patients (46 per 10 000 contacts screened). Among the eligible screened contacts, 1182 (0·7%) refused prophylactic treatment with SDR. Overall, SDR was administered to 151 928 (86·9%) screened contacts. No serious adverse events were reported. Interpretation Post-exposure prophylaxis with SDR is safe; can be integrated into different leprosy control programmes with minimal additional efforts once contact tracing has been established; and is generally well accepted by index patients, their contacts, and health-care workers. The programme has also invigorated local leprosy control through the availability of a prophylactic intervention; therefore, we recommend rolling out SDR in all settings where contact tracing and screening have been established. Funding Novartis Foundation.

Background: In line with the movement restrictions and physical distancing essential for the control of the current global COVID-19 pandemic, the World Health Organization (WHO) recommended postponement of all neglected tropical disease (NTD) control activities which involve community-based surveys, active case-finding and mass drug administration (MDA). This study aimed to evaluate the potential impact of this interruption. Methods: For seven of the NTDs, namely soil-transmitted helminths, schistosomiasis, lymphatic filariasis, onchocerciasis, trachoma, visceral leishmaniasis and human African trypanosomiasis, we use mathematical transmission models to assess the potential impact of the current disruption to programmes on the dynamics of each of these diseases in different endemic settings. We also explore the potential benefit of implementing mitigation strategies once restrictions are relaxed, both in minimising the delays to control targets and reducing longer-term morbidity. Findings: We demonstrate that the impact of the COVID-19 induced interruption in terms of delay to achieving elimination goals is likely to be greatest in those areas where NTD endemicity is highest. We also show that these delays can largely be mitigated by measures such as additional MDA or enhanced case-finding, and that the sooner these mitigation strategies are implemented, the greater the benefit in terms of long-term morbidity reduction. Interpretation: The COVID-19 pandemic has brought infectious disease control to the forefront of global consciousness. It is essential that the NTDs, so long neglected in terms of research and financial support, are not overlooked during the current crisis, and remain a priority in health service planning and funding. Funding Statement: This work was supported by the NTD Modelling Consortium, funded by the Bill and Melinda Gates Foundation (OPP1184344). JT acknowledges joint funding by the UK Medical Research Council (MRC) and the UK Department for International Development (DFID) under the MRC/DFID Concordat agreement which is also part of the EDCTP2 programme supported by the European Union (MR/R015600/1). Declaration of Interests: All authors declare no competing interests.

Background\ud \ud Brazil has the second highest annual number of new leprosy cases. The aim of this study is to formally compare predictions of future new case detection rate (NCDR) trends and the annual probability of NCDR falling below 10/100,000 of four different modelling approaches in four states of Brazil: Rio Grande do Norte, Amazonas, Ceará, Tocantins.\ud \ud Methods\ud \ud A linear mixed model, a back-calculation approach, a deterministic compartmental model and an individual-based model were used. All models were fitted to leprosy data obtained from the Brazilian national database (SINAN). First, models were fitted to the data up to 2011, and predictions were made for NCDR for 2012–2014. Second, data up to 2014 were considered and forecasts of NCDR were generated for each year from 2015 to 2040. The resulting distributions of NCDR and the probability of NCDR being below 10/100,000 of the population for each year were then compared between approaches.\ud \ud Results\ud \ud Each model performed well in model fitting and the short-term forecasting of future NCDR. Long-term forecasting of NCDR and the probability of NCDR falling below 10/100,000 differed between models. All agree that the trend of NCDR will continue to decrease in all states until 2040. Reaching a NCDR of less than 10/100,000 by 2020 was only likely in Rio Grande do Norte. Prediction until 2040 showed that the target was also achieved in Amazonas, while in Ceará and Tocantins the NCDR most likely remain (far) above 10/100,000.\ud \ud Conclusions\ud \ud All models agree that, while incidence is likely to decline, achieving a NCDR below 10/100,000 by 2020 is unlikely in some states. Long-term prediction showed a downward trend with more variation between models, but highlights the need for further control measures to reduce the incidence of new infections if leprosy is to be eliminated.

Objectives The WHO recommends inclusion of post‐exposure chemoprophylaxis with single‐dose rifampicin in national leprosy control programmes. The objective was to estimate the cost of leprosy services at primary care level in two different public‐health settings. Methods Ingredient‐based costing was performed in eight primary health centres (PHCs) purposively selected in the Union Territory of Dadra and Nagar Haveli (DNH) and the Umbergaon block of Valsad district, Gujarat, India. All costs were bootstrapped, and to estimate the variation in total cost under uncertainty, a univariate sensitivity analysis was performed. Results The mean annual cost of providing leprosy services was USD 29 072 in the DNH PHC (95% CI: 22 125–36 020) and USD 11 082 in Umbergaon (95% CI: 8334–13 830). The single largest cost component was human resources: 79% in DNH and 83% in Umbergaon. The unit cost for screening the contact of a leprosy patient was USD 1 in DNH (95% CI: 0.8–1.2) and USD 0.3 in Umbergaon (95% CI: 0.2–0.4). In DNH, the unit cost of delivering single‐dose of rifampicin (SDR) as chemoprophylaxis for contacts was USD 2.9 (95% CI: 2.5–3.7). Conclusions The setting with an enhanced public‐health financing system invests more in leprosy services than a setting with fewer financial resources. In terms of leprosy visits, the enhanced public‐health system is hardly more expensive than the non‐enhanced public‐health system. The unit cost of contact screening is not high, favouring its sustainability in the programme.

Background The country of Kiribati is a small Pacific island nation which had a new case detection rate of 191 per 100,000 in 2016, and is one of the few countries yet to reach the WHO leprosy elimination goal. Chemoprophylaxis of household contacts of new cases, or to the whole population in a highly endemic areas have been found to be effective in reducing new case rates. This study investigated the potential impact of different chemoprophylaxis strategies on future cases in South Tarawa, the main population centre of Kiribati. Methodology The microsimulation model SIMCOLEP was calibrated to simulate the South Tarawa population and past leprosy control activities, and replicate annual new cases from 1989 to 2016. The impact of six different strategies for delivering one round of single dose rifampicin (SDR) chemoprophylaxis to household contacts of new cases and/or one or three rounds of SDR to the whole population was modelled from 2017 to 2030. Principal Findings Our model predicted that continuing the existing control program of high levels of public awareness, passive case detection, and treatment with multidrug treatment would lead to a substantial reduction in cases but this was less effective than all modelled intervention scenarios. Mass chemoprophylaxis led to a faster initial decline in cases than household contact chemoprophylaxis alone, however the decline under the latter was sustained for longer. The greatest cumulative impact was for household contact chemoprophylaxis with three rounds of mass chemoprophylaxis at one-year intervals. Conclusions The results suggest that control of leprosy would be achieved most rapidly with a combination of intensive population-based and household chemoprophylaxis. These findings may be generalisable to other countries where crowding places social contacts as well as household contacts of cases at risk of developing leprosy., Author summary Leprosy rates in Kiribati are some of the highest in the world and it is one of the few countries yet to reach the World Health Organization leprosy elimination goal of a prevalence of less than one case per 10,000 population. The greatest burden is in the capital South Tarawa and the connected islet of Betio. Interest has increased for the use of chemoprophylaxis, the administration of preventive antibiotics to apparently healthy individuals who may be incubating the disease, which has been demonstrated to be effective in both household contacts and the whole population in two recent studies. In this study we used the individual-based model SIMCOLEP to predict the impact of six difference scenarios using single dose rifampicin (SDR) chemoprophylaxis in household contacts and/or the entire population on future new cases in South Tarawa. We found that all chemoprophylaxis strategies were predicted to be more effective than the current control strategy, particularly a combination of household contact chemoprophylaxis alongside three rounds given to the entire population in consecutive years.

Background Income inequalities in sports participation are shaped by a system in which individuals and the environment interact. We developed an agent-based model (ABM) that could represent this system and used it to provide a proof-of-concept of its potential to explore the impact of individual and environmental interventions on reducing inequalities in sports participation. Methods Our ABM simulates sports participation of individuals in the Dutch city of Eindhoven. In the model, sports participation is determined by an individual’s tendency to start sports (at a fitness center, sports club or self-organized), which is influenced by attributes of individuals (i.e. age, sex, income), sports facilities (i.e. price, accessibility) and the social environment (i.e. social cohesion, social influence). Sports facilities can adapt to changes in the demand by closures or startups, which in turn influence the tendency of individuals to participate in sport. We explored the impact of five interventions scenarios. Results Explorative results show that providing health education, increasing the availability of sports facilities, lowering prices of facilities and improving safety levels can increase sports participation and modestly reduce absolute income inequalities in sports participation. The largest gain can be attained through health education, if the effect and reach is sufficiently large. Environmental interventions alone have a modest impact. Marked effects are only achieved after five to 10 years. Conclusions ABMs have much potential to test the population-level effects of various interventions in the context of a system. Our study highlights the challenges of ABM development and reveals gaps in empirical data. With further refinements, our model could aid in understanding and finding optimal pathways to reduce income inequalities in sports participation. Electronic supplementary material The online version of this article (10.1186/s12966-018-0740-y) contains supplementary material, which is available to authorized users.

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., Author summary The annual number of new leprosy cases has been stable in the past decade, indicating that transmission has not been yet been interrupted. As current control seems to be insufficient to bring down the number of cases, there is a need for novel tools to interrupt transmission. A diagnostic that permitted diagnosis of subclinical cases will likely be fundamental to achieve elimination and ultimately eradication. 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. We showed that a diagnostic test for subclinical leprosy could substantially reduce the NCDR in a high, medium and low endemic population. A significant impact could already be achieved at a test sensitivity level of 50%. To effectively reduce the NCDR in the short run, a population survey is preferred over household contact tracing. However, this is only favorable in high endemic settings, as in medium and low endemic settings testing in a population survey requires many more people to be tested and treated to prevent one new leprosy case.

Introduction Individual and environmental factors dynamically interact in shaping income inequalities in healthy food consumption. The agent-based model, Health Behaviors Simulation (HEBSIM), was developed to describe income inequalities in healthy food consumption. It simulates interactions between households and their environment. HEBSIM was used to explore the impact of interventions aimed at reducing food consumption inequalities. Methods HEBSIM includes households and food outlets. Households are characterized by location, composition, income, and preference for food. Decisions about where to shop for food (fruit/vegetable stores, supermarkets, or discount supermarkets) and whether to visit fast food outlets are based on distance, price, and food preference. Food outlets can close and new food outlets can enter the system. Three interventions to reduce healthy food consumption inequalities were tested: (1) eliminating residential segregation; (2) lowering the prices of healthy food; and (3) providing health education. HEBSIM was quantified using data from Statistics Netherlands, Statistics Eindhoven, and the GLOBE study (2011). Results The model mimicked food consumption in Eindhoven. High-income households visited healthy food shops more often than low-income households. Eliminating residential segregation had the largest impact in reducing income inequalities in food consumption, but resulted partly from a worsening in healthy food consumption in high-income households. Lowering prices and health education could also substantially reduce inequalities. Most interventions took 5–10 years to reach their (almost) full effects. Conclusions HEBSIM is a promising tool for studying dynamic interactions between households and their environment and for assessing the impact of interventions on income inequalities in food consumption.

Understanding the spread of smoking cessation and relapse within social networks may offer new approaches to further curb the smoking epidemic. Whether smoking behavior among social network members determines smoking cessation and relapse of adults however, is less known. For this study, longitudinal data of 4623 adults participating in the Dutch Longitudinal Internet Studies for the Social sciences (LISS) panel were collected in March 2013 with a follow-up in 2014. Logistic regression was used to examine the association between the proportion of smokers in social networks, and (1) smoking cessation (n = 762) and (2) smoking relapse (n = 1905). Analyses were adjusted for the size of the network, age, sex, and education. Respondents with the largest proportion of smokers in their social network were less likely to quit smoking (OR = 0.25; 95% CI = 0.11–0.66) and more likely to experience a relapse (6.08; 3.01–12.00). Smoking cessation and relapse were most strongly associated with the proportion of smokers among household members and friends. The proportion of smokers in family outside the household was not related to smoking cessation and smoking relapse. In conclusion, smoking behavior in social networks, especially among household members and friends, is strongly associated with smoking cessation and relapse. These findings further support the spread of smoking within social networks, and provide evidence for network-based interventions, particularly including household members and friends.

Background Leprosy remains a public health problem in Brazil. Although the overall number of new cases is declining, there are still areas with a high disease burden, such as Pará State in the north of the country. We aim to predict future trends in new case detection rate (NCDR) and explore the potential impact of contact tracing and chemoprophylaxis on NCDR in Pará State. Methods We used SIMCOLEP, an existing individual-based model for the transmission and control of M. leprae, in a population structured by households. The model was quantified to simulate the population and observed NCDR of leprosy in Pará State for the period 1990 to 2014. The baseline scenario was the current control program, consisting of multidrug therapy, passive case detection, and active case detection from 2003 onwards. Future projections of the NCDR were made until 2050 given the continuation of the current control program (i.e. baseline). We further investigated the potential impact of two scenarios for future control of leprosy: 1) discontinuation of contact tracing; and 2) continuation of current control in combination with chemoprophylaxis. Both scenarios started in 2015 and were projected until 2050. Results The modelled NCDR in Pará State after 2014 shows a continuous downward trend, reaching the official elimination target of 10 cases per 100,000 population by 2030. The cessation of systematic contact tracing would not result in a higher NCDR in the long run. Systematic contact tracing in combination with chemoprophylaxis for contacts would reduce the NCDR by 40% and bring attainment of the elimination target two years forward to 2028. Conclusion The NCDR of leprosy continues to decrease in Pará State. Elimination of leprosy as a public health problem could possibly be achieved around 2030, if the current control program is maintained. Providing chemoprophylaxis would decrease the NCDR further and would bring elimination forward by two years., Author Summary Leprosy remains a public health problem in Brazil. With over 30,000 new cases detected annually, it has the second-largest number of leprosy cases detected worldwide. Although the overall number of new cases is declining, there are still areas with a high disease burden, such as Pará State. In this study, we used the individual-based model SIMCOLEP to predict the future trend of the new case detection rate of leprosy (NCDR) in Pará State given the current control strategy. Additionally, we explored the potential impact of contact tracing and chemoprophylaxis on the NCDR. Our results show that the NCDR continues to decrease in Para State, reaching elimination around 2030. Contact tracing alone would not further reduce the NCDR. However, when contact tracing is combined with chemoprophylaxis the NCDR would be reduced up to 40% and elimination could be brought forward by two years.

Background The London Declaration (2012) was formulated to support and focus the control and elimination of ten neglected tropical diseases (NTDs), with targets for 2020 as formulated by the WHO Roadmap. Five NTDs (lymphatic filariasis, onchocerciasis, schistosomiasis, soil-transmitted helminths and trachoma) are to be controlled by preventive chemotherapy (PCT), and four (Chagas’ disease, human African trypanosomiasis, leprosy and visceral leishmaniasis) by innovative and intensified disease management (IDM). Guinea worm, virtually eradicated, is not considered here. We aim to estimate the global health impact of meeting these targets in terms of averted morbidity, mortality, and disability adjusted life years (DALYs). Methods The Global Burden of Disease (GBD) 2010 study provides prevalence and burden estimates for all nine NTDs in 1990 and 2010, by country, age and sex, which were taken as the basis for our calculations. Estimates for other years were obtained by interpolating between 1990 (or the start-year of large-scale control efforts) and 2010, and further extrapolating until 2030, such that the 2020 targets were met. The NTD disease manifestations considered in the GBD study were analyzed as either reversible or irreversible. Health impacts were assessed by comparing the results of achieving the targets with the counterfactual, construed as the health burden had the 1990 (or 2010 if higher) situation continued unabated. Principle Findings/Conclusions Our calculations show that meeting the targets will lead to about 600 million averted DALYs in the period 2011–2030, nearly equally distributed between PCT and IDM-NTDs, with the health gain amongst PCT-NTDs mostly (96%) due to averted disability and amongst IDM-NTDs largely (95%) from averted mortality. These health gains include about 150 million averted irreversible disease manifestations (e.g. blindness) and 5 million averted deaths. Control of soil-transmitted helminths accounts for one third of all averted DALYs. We conclude that the projected health impact of the London Declaration justifies the required efforts., Author Summary Neglected tropical diseases (NTDs) are a group of infectious diseases that occur mostly in poor, warm countries. NTDs are caused by various bacteria and parasites, such as worms. They can either be cured or prevented through drugs and other interventions, such as control of insects that spread the infection. The London Declaration is a statement by various organizations, including the World Health Organization (WHO) and pharmaceutical companies that donate the necessary drugs. The declaration endorses targets for disease reductions by 2020, as recently formulated in the WHO Roadmap, to be achieved by rigorous application of available interventions. We explore how much health can be gained if these targets are indeed achieved. We estimate that in such case 5 million deaths can be averted before 2030 and also that huge reductions in ill-health and disability can be realized. Over the period 2011–2030, a total health gain would be accomplished of about 600 million disability adjusted life years (DALYs) averted. DALYs are a measure of disease burden, consisting of life years lost and years lived with disability. This enormous health gain seems to justify similar investments as for e.g. HIV or malaria control.

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.

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.

Background: Every year more than 200,000 new leprosy cases are registered globally. This number has been fairly stable over the past 8 years. WHO has set a target to interrupt the transmission of leprosy globally by 2020. The aim of this study is to investigate whether this target, interpreted as global elimination, is feasible given the current control strategy. We focus on the three most important endemic countries, India, Brazil and Indonesia, which together account for more than 80 % of all newly registered leprosy cases. Methods: We used the existing individual-based model SIMCOLEP to predict future trends of leprosy incidence given the current control strategy in each country. SIMCOLEP simulates the spread of M. leprae in a population that is structured in households. Current control consists of passive and active case detection, and multidrug therapy (MDT). Predictions of leprosy incidence were made for each country as well as for one high-endemic region within each country: Chhattisgarh (India), Para State (Brazil) and Madura (Indonesia). Data for model quantification came from: National Leprosy Elimination Program (India), SINAN database (Brazil), and Netherlands Leprosy Relief (Indonesia). Results: Our projections of future leprosy incidence all show a downward trend. In 2020, the country-level leprosy incidence has decreased to 6.2, 6.1 and 3.3 per 100,000 in India, Brazil and Indonesia, respectively, meeting the elimination target of less than 10 per 100,000. However, elimination may not be achieved in time for the high-endemic regions. The leprosy incidence in 2020 is predicted to be 16.2, 21.1 and 19.3 per 100,000 in Chhattisgarh, Para and Madura, respectively, and the target may only be achieved in another 5 to 10 years. Conclusions: Our predictions show that although country-level elimination is reached by 2020, leprosy is likely to remain a problem in the high-endemic regions (i.e. states, districts and provinces with multimillion populations), which account for most of the cases in a country.

SUMMARYWe argue that the spread of unhealthy behaviour shows marked similarities with infectious diseases. It is therefore interesting and challenging to use infectious disease methodologies for studying the spread and control of unhealthy behaviour. This would be a great addition to current methods, because it allows taking into account the dynamics of individual interactions and the social environment at large. In particular, the application of individual-based modelling holds great promise to address some major public health questions.

Individual and environmental factors dynamically interact in shaping income inequalities in healthy food consumption. The agent-based model, Health Behaviors Simulation (HEBSIM), was developed to describe income inequalities in healthy food consumption. It simulates interactions between households and their environment. HEBSIM was used to explore the impact of interventions aimed at reducing food consumption inequalities.HEBSIM includes households and food outlets. Households are characterized by location, composition, income, and preference for food. Decisions about where to shop for food (fruit/vegetable stores, supermarkets, or discount supermarkets) and whether to visit fast food outlets are based on distance, price, and food preference. Food outlets can close and new food outlets can enter the system. Three interventions to reduce healthy food consumption inequalities were tested: (1) eliminating residential segregation; (2) lowering the prices of healthy food; and (3) providing health education. HEBSIM was quantified using data from Statistics Netherlands, Statistics Eindhoven, and the GLOBE study (2011).The model mimicked food consumption in Eindhoven. High-income households visited healthy food shops more often than low-income households. Eliminating residential segregation had the largest impact in reducing income inequalities in food consumption, but resulted partly from a worsening in healthy food consumption in high-income households. Lowering prices and health education could also substantially reduce inequalities. Most interventions took 5-10 years to reach their (almost) full effects.HEBSIM is a promising tool for studying dynamic interactions between households and their environment and for assessing the impact of interventions on income inequalities in food consumption.

We investigated whether the prevalence of health-related behaviors and overweight in neighborhoods is associated with changes in smoking, sports participation and overweight over 13 years of follow-up in Dutch adults residing in 86 neighborhoods of Eindhoven in 1991. We showed that living in neighborhoods with a high prevalence of non-smoking, no sports participation and overweight increased the odds of quitting smoking, quitting sports and becoming overweight. After adjustments for age, gender, education and neighborhood deprivation this association remained significant for becoming overweight. Neighborhood prevalence of health-related behaviors and overweight appears to be a currently neglected but relevant determinant of changes in health-related behaviors.