Improved Assessment of Schistosoma Community Infection Through Data Resampling Method.

Background: The conventional diagnostic for Schistosoma mansoni infection is stool microscopy with the Kato-Katz (KK) technique to detect eggs. Its outcomes are highly variable on a day-to-day basis and may lead to biased estimates of community infection used to inform public health programs. Our goal is to develop a resampling method that leverages data from a large-scale randomized trial to accurately predict community infection. Methods: We developed a resampling method that provides unbiased community estimates of prevalence, intensity and other statistics for S mansoni infection when a community survey is conducted using KK stool microscopy with a single sample per host. It leverages a large-scale data set, collected in the Schistosomiasis Consortium for Operational Research and Evaluation (SCORE) project, and allows linking single-stool specimen community screening to its putative multiday "true statistics." Results: SCORE data analysis reveals the limited sensitivity of KK stool microscopy and systematic bias of single-day community testing versus multiday testing; for prevalence estimate, it can fall up to 50% below the true value. The proposed SCORE cluster method reduces systematic bias and brings the estimated prevalence values within 5%-10% of the true value. This holds for a broad swath of transmission settings, including SCORE communities, and other data sets. Conclusions: Our SCORE cluster method can markedly improve the S mansoni prevalence estimate in settings using stool microscopy.

High urban NOx triggers a substantial chemical downward flux of ozone.

Nitrogen oxides (NOx) play a central role in catalyzing tropospheric ozone formation. Nitrogen dioxide (NO2) has recently reemerged as a key target for air pollution control measures, and observational evidence points toward a limited understanding of ozone in high-NOx environments. A complete understanding of the mechanisms controlling the rapid atmospheric cycling between ozone (O3)-nitric oxide (NO)-NO2 in high-NOx regimes at the surface is therefore paramount but remains challenging because of competing dynamical and chemical effects. Here, we present long-term eddy covariance measurements of O3, NO, and NO2, over an urban area, that allow disentangling important physical and chemical processes. When generalized, our findings suggest that the depositional O3 flux near the surface in urban environments is negligible compared to the flux caused by chemical conversion of O3. This leads to an underestimation of the Leighton ratio and is a key process for modulating urban NO2 mixing ratios. As a consequence, primary NO2 emissions have been significantly overestimated.

Schistosoma Transmission in a Dynamic Seasonal Environment and its Impact on the Effectiveness of Disease Control.

BACKGROUND: A seasonal transmission environment including seasonal variation of snail population density and human-snail contact patterns can affect the dynamics of Schistosoma infection and the success of control interventions. In projecting control outcomes, conventional modeling approaches have often ignored seasonality by using simplified intermediate-host modeling, or by restricting seasonal effects through use of yearly averaging. METHODS: We used mathematical analysis and numerical simulation to estimate the impact of seasonality on disease dynamics and control outcomes, and to evaluate whether seasonal averaging or intermediate-host reduction can provide reliable predictions of control outcomes. We also examined whether seasonality could be used as leverage in creation of effective control strategies. RESULTS: We found models that used seasonal averaging could grossly overestimate infection burden and underestimate control outcomes in highly seasonal environments. We showed that proper intraseasonal timing of control measures could make marked improvement on the long-term burden reduction for Schistosoma transmission control, and we identified the optimal timing for each intervention. Seasonal snail control, implemented alone, was less effective than mass drug administration, but could provide additive impact in reaching control and elimination targets. CONCLUSIONS: Seasonal variation makes Schistosoma transmission less sustainable and easier to control than predicted by earlier modeling studies.

Individual-based modeling of COVID-19 transmission in college communities.

The ongoing COVID-19 pandemic has created major public health and socio-economic challenges across the United States. Among them are challenges to the educational system where college administrators are struggling with the questions of how to mitigate the risk and spread of diseases on their college campus. To help address this challenge, we developed a flexible computational framework to model the spread and control of COVID-19 on a residential college campus. The modeling framework accounts for heterogeneity in social interactions, activities, environmental and behavioral risk factors, disease progression, and control interventions. The contribution of mitigation strategies to disease transmission was explored without and with interventions such as vaccination, quarantine of symptomatic cases, and testing. We show that even with high vaccination coverage (90%) college campuses may still experience sizable outbreaks. The size of the outbreaks varies with the underlying environmental and socio-behavioral risk factors. Complementing vaccination with quarantine and mass testing was shown to be paramount for preventing or mitigating outbreaks. Though our quantitative results are likely provisional on our model assumptions, sensitivity analysis confirms the robustness of their qualitative nature.

SARS-CoV-2 transmission and control in a hospital setting: an individual-based modelling study.

Development of strategies for mitigating the severity of COVID-19 is now a top public health priority. We sought to assess strategies for mitigating the COVID-19 outbreak in a hospital setting via the use of non-pharmaceutical interventions. We developed an individual-based model for COVID-19 transmission in a hospital setting. We calibrated the model using data of a COVID-19 outbreak in a hospital unit in Wuhan. The calibrated model was used to simulate different intervention scenarios and estimate the impact of different interventions on outbreak size and workday loss. The use of high-efficacy facial masks was shown to be able to reduce infection cases and workday loss by 80% (90% credible interval (CrI): 73.1-85.7%) and 87% (CrI: 80.0-92.5%), respectively. The use of social distancing alone, through reduced contacts between healthcare workers, had a marginal impact on the outbreak. Our results also indicated that a quarantine policy should be coupled with other interventions to achieve its effect. The effectiveness of all these interventions was shown to increase with their early implementation. Our analysis shows that a COVID-19 outbreak in a hospital's non-COVID-19 unit can be controlled or mitigated by the use of existing non-pharmaceutical measures.

Application of Schistosomiasis Consortium for Operational Research and Evaluation Study Findings to Refine Predictive Modeling of Schistosoma mansoni and Schistosoma haematobium Control in Sub-Saharan Africa.

An essential mission of the Schistosomiasis Consortium for Operational Research and Evaluation (SCORE) was to help inform global health practices related to the control and elimination of schistosomiasis. To provide more accurate, evidence-based projections of the most likely impact of different control interventions, whether implemented alone or in combination, SCORE supported mathematical modeling teams to provide simulations of community-level Schistosoma infection outcomes in the setting of real or hypothetical programs implementing multiyear mass drug administration (MDA) for parasite control. These models were calibrated using SCORE experience with Schistosoma mansoni and Schistosoma haematobium gaining and sustaining control studies, and with data from comparable programs that used community-based or school-based praziquantel MDA in other parts of sub-Saharan Africa. From 2010 to 2019, models were developed and refined, first to project the likely SCORE control outcomes, and later to more accurately reflect impact of MDA across different transmission settings, including the role of snail ecology and the impact of seasonal rainfall on snail abundance. Starting in 2014, SCORE modeling projections were also compared with the models of colleagues in the Neglected Tropical Diseases Modelling Consortium. To explore further possible improvement to program-based control, later simulations examined the cost-effectiveness of combining MDA with environmental snail control, and the utility of early impact assessment to more quickly identify persistent hot spots of transmission. This article provides a nontechnical summary of the 11 SCORE-related modeling projects and provides links to the original open-access articles describing model development and projections relevant to schistosomiasis control policy.

Risk factors of SARS-CoV-2 infection in healthcare workers: a retrospective study of a nosocomial outbreak.

BACKGROUND: Healthcare workers (HCWs) are at the forefront of fighting against the COVID-19 pandemic. However, they are at high risk of acquiring the pathogen from infected patients and transmitting to other HCWs. We aimed to investigate risk factors for nosocomial COVID-19 infection among HCWs in a non-COVID-19 hospital yard. METHODS: Retrospective data collection on demographics, lifestyles, contact status with infected subjects for 118 HCWs (including 12 COVID-19 HCWs) at Union Hospital of Wuhan, China. Sleep quality and working pressure were evaluated by the Pittsburgh Sleep Quality Index (PSQI) and The Nurse Stress Index (NSI), respectively. The follow-up duration was from Dec 25, 2019, to Feb 15, 2020. RESULTS: A high proportion of COVID-19 HCWs had engaged in night shift-work (75.0% vs. 40.6%) and felt working under pressure (66.7% vs. 32.1%) than uninfected HCWs. SARS-CoV-2 infected HCWs had significantly higher scores of PSQI and NSI than uninfected HCWs (P < 0.001). Specifically, scores of 5 factors (sleep quality, sleep time, sleep efficiency, sleep disorder, and daytime dysfunction) in PSQI were higher among infected HCWs. For NSI, its 5 subscales (nursing profession and work, workload and time allocation, working environment and resources, patient care, management and interpersonal relations) were all higher in infected than uninfected nurse. Furthermore, total scores of PSQI (HR = 2.97, 95%CI = 1.86-4.76; P <0.001) and NSI (HR = 4.67, 95%CI = 1.42-15.45; P = 0.011) were both positively associated with the risk of SARS-CoV-2 infection. CONCLUSION: Our analysis shows that poor sleep quality and higher working pressure may increase the risk of nosocomial SARS-CoV-2 infection among HCWs.

Improving public health control of schistosomiasis with a modified WHO strategy: a model-based comparison study.

BACKGROUND: Schistosomiasis is endemic in many low-income and middle-income countries. To reduce infection-associated morbidity, WHO has published guidelines for control of schistosomiasis based on targeted mass drug administration (MDA) and, in 2017, on supplemental snail control. We compared the current WHO guideline-based strategies from 2012 to an alternative, adaptive decision making framework for control in heterogeneous environments, to estimate their predicted relative effectiveness and time to achievement of defined public health goals. METHODS: In this model-based comparison study, we adapted an established transmission model for Schistosoma infection that couples local human and snail populations and includes aspects of snail ecology and parasite biology. We calibrated the model using data from high-risk, moderate-risk, and lower-risk rural villages in Kenya, and then simulated control via MDA. We compared 2012 WHO guidelines with a modified adaptive strategy that tested a lower-prevalence threshold for MDA and shorter intervals between implementation, evaluation, and modification. We also explored the addition of snail control to this modified strategy. The primary outcomes were the proportion of simulations that achieved the WHO targets in children aged 5-14 years of less than 5% (2020 morbidity control goal) and less than 1% (2025 elimination as a public health problem goal) heavy infection and the mean duration of treatment required to achieve these goals. FINDINGS: In high-risk communities (80% baseline prevalence), current WHO strategies for MDA were not predicted to achieve morbidity control (<5% prevalence of heavy infections) in 80% of simulations over a 10-year period, whereas the modified adaptive strategy was predicted to achieve this goal in over 50% of simulations within 5 years. In low-risk and moderate-risk communities, current WHO guidelines from 2012 were predicted to achieve morbidity control in most simulations (96% in low-risk and 41% for moderate-risk), although the proposed adaptive strategy reached this goal in a shorter period (mean reduction of 5 years). The model predicted that the addition of snail control to the proposed adaptive strategy would achieve morbidity control in all high-risk communities, and 54% of communities could reach the goal for elimination as a public health problem (<1% heavy infection) within 7 years. INTERPRETATION: The modified adaptive decision making framework is predicted to be more effective than the current WHO guidelines in reaching 2025 public health goals, especially for high-prevalence regions. Modifications in current guidelines could reduce the time and resources needed for countries who are currently working on achieving public health goals against schistosomiasis. FUNDING: University of Georgia Research Foundation, The Bill & Melinda Gates Foundation, and the Medical Scientist Training Program at Stanford University School of Medicine.

Are We on Our Way to Achieving the 2020 Goals for Schistosomiasis Morbidity Control Using Current World Health Organization Guidelines?

Background: Schistosomiasis remains an endemic parasitic disease affecting millions of people around the world. The World Health Organization (WHO) has set goals of controlling morbidity to be reached by 2020, along with elimination as a public health problem in certain regions by 2025. Mathematical models of parasite transmission and treatment impact have been developed to assist in controlling the morbidity caused by schistosomiasis. These models can inform and guide implementation policy for mass drug administration programs, and help design monitoring and evaluation activities. Methods: We use these models to predict whether the guidelines set by the WHO are on track for achieving their 2020 goal for the control of morbidity, specifically for Schistosoma mansoni. We examine whether programmatic adaptations; namely increases in treatment coverage and/or expansion to adult inclusion in treatment, will improve the likelihood of reaching the WHO goals. Results: We find that in low-prevalence settings, the goals are likely to be attainable under current WHO guidelines, but in moderate to high-prevalence settings, the goals are less likely to be achieved unless treatment coverage is increased and expanded to at least 85% for school-aged children and 40% for adults. Conclusions: To improve the likelihood of reaching the WHO goals, programmatic adaptations are required, particularly for moderate- to high-prevalence settings. Furthermore, improvements in adherence to treatment, potential development of candidate vaccines, and enhanced snail control and WASH (water, sanitation, and hygiene) measures will all assist in achieving the goals.

The human-snail transmission environment shapes long term schistosomiasis control outcomes: Implications for improving the accuracy of predictive modeling.

INTRODUCTION: Schistosomiasis is a chronic parasitic trematode disease that affects over 240 million people worldwide. The Schistosoma lifecycle is complex, involving transmission via specific intermediate-host freshwater snails. Predictive mathematical models of Schistosoma transmission have often chosen to simplify or ignore the details of environmental human-snail interaction in their analyses. Schistosome transmission models now aim to provide better precision for policy planning of elimination of transmission. This heightens the importance of including the environmental complexity of vector-pathogen interaction in order to make more accurate projections. METHODOLOGY AND PRINCIPAL FINDINGS: We propose a nonlinear snail force of infection (FOI) that takes into account an intermediate larval stage (miracidium) and snail biology. We focused, in particular, on the effects of snail force of infection (FOI) on the impact of mass drug administration (MDA) in human communities. The proposed (modified) model was compared to a conventional model in terms of their predictions. A longitudinal dataset generated in Kenya field studies was used for model calibration and validation. For each sample community, we calibrated modified and conventional model systems, then used them to model outcomes for a range of MDA regimens. In most cases, the modified model predicted more vigorous post-MDA rebound, with faster relapse to baseline levels of infection. The effect was pronounced in higher risk communities. When compared to observed data, only the modified system was able to successfully predict persistent rebound of Schistosoma infection. CONCLUSION AND SIGNIFICANCE: The observed impact of varying location-specific snail inputs sheds light on the diverse MDA response patterns noted in operational research on schistosomiasis control, such as the recent SCORE project. Efficiency of human-to-snail transmission is likely to be much higher than predicted by standard models, which, in practice, will make local elimination by implementation of MDA alone highly unlikely, even over a multi-decade period.

Impact and cost-effectiveness of snail control to achieve disease control targets for schistosomiasis.

Schistosomiasis is a parasitic disease that affects over 240 million people globally. To improve population-level disease control, there is growing interest in adding chemical-based snail control interventions to interrupt the lifecycle of Schistosoma in its snail host to reduce parasite transmission. However, this approach is not widely implemented, and given environmental concerns, the optimal conditions for when snail control is appropriate are unclear. We assessed the potential impact and cost-effectiveness of various snail control strategies. We extended previously published dynamic, age-structured transmission and cost-effectiveness models to simulate mass drug administration (MDA) and focal snail control interventions against Schistosoma haematobium across a range of low-prevalence (5-20%) and high-prevalence (25-50%) rural Kenyan communities. We simulated strategies over a 10-year period of MDA targeting school children or entire communities, snail control, and combined strategies. We measured incremental cost-effectiveness in 2016 US dollars per disability-adjusted life year and defined a strategy as optimally cost-effective when maximizing health gains (averted disability-adjusted life years) with an incremental cost-effectiveness below a Kenya-specific economic threshold. In both low- and high-prevalence settings, community-wide MDA with additional snail control reduced total disability by an additional 40% compared with school-based MDA alone. The optimally cost-effective scenario included the addition of snail control to MDA in over 95% of simulations. These results support inclusion of snail control in global guidelines and national schistosomiasis control strategies for optimal disease control, especially in settings with high prevalence, "hot spots" of transmission, and noncompliance to MDA.

Quantitative assessment of the impact of partially protective anti-schistosomiasis vaccines.

BACKGROUND: Mass drug administration (MDA) of praziquantel has been the intervention of choice against schistosomiasis but with limited success in interrupting the transmission. The development of anti-Schistosoma vaccines is underway. Our objective is to quantify the population-level impact of anti-Schistosoma vaccines when administered alone and in combination with mass drug administration (MDA) and determine factors in vaccine design and public health implementation that optimize vaccination role in schistosomiasis control and elimination. METHODS AND FINDINGS: We developed a deterministic compartmental model simulation of schistosomiasis transmission in a high-risk Kenyan community, including stratification by age, parasite burden, and vaccination status. The modeled schistosomiasis vaccines differed in terms of vaccine duration of protection (durability) and three biological efficacies. These are vaccine susceptibility effect (SE) of reducing person's susceptibility to Schistosoma acquisition, vaccine mortality effect (ME) of reducing established worm burden and vaccine fecundity effect (FE) of reducing egg release by mature worms. We quantified the population-level impact of vaccination over two decades under diverse vaccination schemes (childhood vs. mass campaigns), with different age-targeting scenarios, different risk settings, and with combined intervention with MDA. We also assessed the sensitivity of our predictions to uncertainties in model parameters. Over two decades, our base case vaccine with 80% SE, FE, and ME efficacies, 10 years' durability, provided by mass vaccination every 10 years, reduced host prevalence, mean intensity, incidence, and patent snail prevalence to 31%, 20 eggs/10-ml sample/person, 0.87 worm/person-year, and 0.74%, from endemic-state values of 71%, 152, 3.3, and 0.98%, respectively. Lower impact was found when coverage did not encompass all potential contaminators, and childhood-only vaccination schemes showed delayed and lower impact. In lower prevalence settings, the base case vaccine generated a proportionately smaller impact. A substantially larger vaccine program effect was generated when MDA + mass vaccination was provided every 5 years, which could be achieved by an MDA-only program only if drug was offered annually. Vaccine impact on schistosomiasis transmission was sensitive to a number of parameters including vaccine efficacies, human contact rates with water, human density, patent snails' rate of patency and lifespan, and force of infection to snails. CONCLUSIONS: To be successful a vaccine-based control strategy will need a moderately to highly effective formulation combined with early vaccination of potential contaminators and aggressive coverage in repeated rounds of mass vaccination. Compared to MDA-only program, vaccination combined with MDA accelerates and prolongs the impact by reducing the acquisition of new worms and reducing egg release from residual worms.

Spatial Effects on the Multiplicity of Plasmodium falciparum Infections.

As malaria is being pushed back on many frontiers and global case numbers are declining, accurate measurement and prediction of transmission becomes increasingly difficult. Low transmission settings are characterised by high levels of spatial heterogeneity, which stands in stark contrast to the widely used assumption of spatially homogeneous transmission used in mathematical transmission models for malaria. In the present study an individual-based mathematical malaria transmission model that incorporates multiple parasite clones, variable human exposure and duration of infection, limited mosquito flight distance and most importantly geographically heterogeneous human and mosquito population densities was used to illustrate the differences between homogeneous and heterogeneous transmission assumptions when aiming to predict surrogate indicators of transmission intensity such as population parasite prevalence or multiplicity of infection (MOI). In traditionally highly malaria endemic regions where most of the population harbours malaria parasites, humans are often infected with multiple parasite clones. However, studies have shown also in areas with low overall parasite prevalence, infection with multiple parasite clones is a common occurrence. Mathematical models assuming homogeneous transmission between humans and mosquitoes cannot explain these observations. Heterogeneity of transmission can arise from many factors including acquired immunity, body size and occupational exposure. In this study, we show that spatial heterogeneity has a profound effect on predictions of MOI and parasite prevalence. We illustrate, that models assuming homogeneous transmission underestimate average MOI in low transmission settings when compared to field data and that spatially heterogeneous models predict stable transmission at much lower overall parasite prevalence. Therefore it is very important that models used to guide malaria surveillance and control strategies in low transmission and elimination settings take into account the spatial features of the specific target area, including human and mosquito vector distribution.

Refined stratified-worm-burden models that incorporate specific biological features of human and snail hosts provide better estimates of Schistosoma diagnosis, transmission, and control.

BACKGROUND: Schistosoma parasites sustain a complex transmission process that cycles between a definitive human host, two free-swimming larval stages, and an intermediate snail host. Multiple factors modify their transmission and affect their control, including heterogeneity in host populations and environment, the aggregated distribution of human worm burdens, and features of parasite reproduction and host snail biology. Because these factors serve to enhance local transmission, their inclusion is important in attempting accurate quantitative prediction of the outcomes of schistosomiasis control programs. However, their inclusion raises many mathematical and computational challenges. To address these, we have recently developed a tractable stratified worm burden (SWB) model that occupies an intermediate place between simpler deterministic mean worm burden models and the very computationally-intensive, autonomous agent models. METHODS: To refine the accuracy of model predictions, we modified an earlier version of the SWB by incorporating factors representing essential in-host biology (parasite mating, aggregation, density-dependent fecundity, and random egg-release) into demographically structured host communities. We also revised the snail component of the transmission model to reflect a saturable form of human-to-snail transmission. The new model allowed us to realistically simulate overdispersed egg-test results observed in individual-level field data. We further developed a Bayesian-type calibration methodology that accounted for model and data uncertainties. RESULTS: The new model methodology was applied to multi-year, individual-level field data on S. haematobium infections in coastal Kenya. We successfully derived age-specific estimates of worm burden distributions and worm fecundity and crowding functions for children and adults. Estimates from the new SWB model were compared with those from the older, simpler SWB with some substantial differences noted. We validated our new SWB estimates in prediction of drug treatment-based control outcomes for a typical Kenyan community. CONCLUSIONS: The new version of the SWB model provides a better tool to predict the outcomes of ongoing schistosomiasis control programs. It reflects parasite features that augment and perpetuate transmission, while it also readily incorporates differences in diagnostic testing and human sub-population differences in treatment coverage. Once extended to other Schistosoma species and transmission environments, it will provide a useful and efficient tool for planning control and elimination strategies.

Quantitative analyses and modelling to support achievement of the 2020 goals for nine neglected tropical diseases.

Quantitative analysis and mathematical models are useful tools in informing strategies to control or eliminate disease. Currently, there is an urgent need to develop these tools to inform policy to achieve the 2020 goals for neglected tropical diseases (NTDs). In this paper we give an overview of a collection of novel model-based analyses which aim to address key questions on the dynamics of transmission and control of nine NTDs: Chagas disease, visceral leishmaniasis, human African trypanosomiasis, leprosy, soil-transmitted helminths, schistosomiasis, lymphatic filariasis, onchocerciasis and trachoma. Several common themes resonate throughout these analyses, including: the importance of epidemiological setting on the success of interventions; targeting groups who are at highest risk of infection or re-infection; and reaching populations who are not accessing interventions and may act as a reservoir for infection,. The results also highlight the challenge of maintaining elimination 'as a public health problem' when true elimination is not reached. The models elucidate the factors that may be contributing most to persistence of disease and discuss the requirements for eventually achieving true elimination, if that is possible. Overall this collection presents new analyses to inform current control initiatives. These papers form a base from which further development of the models and more rigorous validation against a variety of datasets can help to give more detailed advice. At the moment, the models' predictions are being considered as the world prepares for a final push towards control or elimination of neglected tropical diseases by 2020.

Modelling control of Schistosoma haematobium infection: predictions of the long-term impact of mass drug administration in Africa.

BACKGROUND: Effective control of schistosomiasis remains a challenging problem for endemic areas of the world. Given knowledge of the biology of transmission and past experience with mass drug administration (MDA) programs, it is important to critically evaluate the likelihood that MDA programs will achieve substantial reductions in Schistosoma prevalence. In implementing the World Health Organization Roadmap for Neglected Tropical Diseases it would useful for policymaking to model projections of the status of Schistosoma control in MDA-treated areas in the next 5-10 years. METHODS: Calibrated mathematical models were used to project the effects of different frequency and coverage of MDA for schistosomiasis haematobia control in present-day endemic communities, taking into account uncertainties of parasite biology and input data. The modeling approach in this analysis was the Stratified Worm Burden model developed in our earlier works, calibrated using data from longitudinal S. haematobium control trials in Kenya. RESULTS: Model-based simulations of MDA control in typical low-risk and higher-risk communities indicated that infection prevalence can be substantially reduced within 10 years only when there is a high degree of community participation (>70 %) with at least annual MDA. Significant risk for re-emergence of infection remains if MDA is suspended. CONCLUSIONS: In a stable (stationary) ecosystem, Schistosoma reproduction and transmission are sufficiently robust that the process of human infection continues, even under pressure from aggressive MDA. MDA alone is unlikely to interrupt transmission, and once mass treatment is suspended, the prevalence of human infection is likely to rebound to pre-control levels over a period of 25-30 years. MDA success in achieving very low levels of infection prevalence is highly dependent on treatment coverage and frequency within the local human population, and requires that both adults and children be included in drug delivery coverage. Ultimately, supplemental snail control and significant improvements in sanitation will be required to achieve full control of schistosomiasis by elimination of ongoing Schistosoma transmission.

Population biology of Schistosoma mating, aggregation, and transmission breakpoints: more reliable model analysis for the end-game in communities at risk.

Mathematical modeling is widely used for predictive analysis of control options for infectious agents. Challenging problems arise for modeling host-parasite systems having complex life-cycles and transmission environments. Macroparasites, like Schistosoma, inhabit highly fragmented habitats that shape their reproductive success and distribution. Overdispersion and mating success are important factors to consider in modeling control options for such systems. Simpler models based on mean worm burden (MWB) formulations do not take these into account and overestimate transmission. Proposed MWB revisions have employed prescribed distributions and mating factor corrections to derive modified MWB models that have qualitatively different equilibria, including 'breakpoints' below which the parasite goes to extinction, suggesting the possibility of elimination via long-term mass-treatment control. Despite common use, no one has attempted to validate the scope and hypotheses underlying such MWB approaches. We conducted a systematic analysis of both the classical MWB and more recent "stratified worm burden" (SWB) modeling that accounts for mating and reproductive hurdles (Allee effect). Our analysis reveals some similarities, including breakpoints, between MWB and SWB, but also significant differences between the two types of model. We show the classic MWB has inherent inconsistencies, and propose SWB as a reliable alternative for projection of long-term control outcomes.

Projecting the long-term impact of school- or community-based mass-treatment interventions for control of Schistosoma infection.

BACKGROUND: Schistosomiasis remains a significant health burden in many areas of the world. Morbidity control, focused on limiting infection intensity through periodic delivery of anti-schistosomal medicines, is the thrust of current World Health Organization guidelines (2006) for reduction of Schistosoma-related disease. A new appreciation of the lifetime impact of repeated Schistosoma infection has directed attention toward strategies for greater suppression of parasite infection per se, with the goal of transmission interruption. Variations in drug schedules involving increased population coverage and/or treatment frequency are now undergoing field trials. However, their relative effectiveness in long-term infection suppression is presently unknown. METHODOLOGY/PRINCIPAL FINDINGS: Our study used available field data to calibrate advanced network models of village-level Schistosoma transmission to project outcomes of six different community- or school age-based programs, as compared to the impact of current 2006 W.H.O. recommended control strategies. We then scored the number of years each of 10 typical villages would remain below 10% infection prevalence (a practicable level associated with minimal prevalence of disease). All strategies that included four annual treatments effectively reduced community prevalence to less than 10%, while programs having yearly gaps ('holidays') failed to reach this objective in half of the communities. Effective post-program suppression of infection prevalence persisted in half of the 10 villages for 7-10 years, whereas in five high-risk villages, program effects on prevalence lasted zero to four years only. CONCLUSIONS/SIGNIFICANCE: At typical levels of treatment adherence (60 to 70%), current WHO recommendations will likely not achieve effective suppression of Schistosoma prevalence unless implemented for ≥6 years. Following more aggressive 4 year annual intervention, some communities may be able to continue without further intervention for 8-10 years, while in higher-risk communities, annual treatment may prove necessary until eco-social factors fostering transmission are removed. Effective ongoing surveillance and locally targeted annual intervention must then become their mainstays of control.

Mathematical modeling of malaria infection with innate and adaptive immunity in individuals and agent-based communities.

BACKGROUND: Agent-based modeling of Plasmodium falciparum infection offers an attractive alternative to the conventional Ross-Macdonald methodology, as it allows simulation of heterogeneous communities subjected to realistic transmission (inoculation patterns). METHODOLOGY/PRINCIPAL FINDINGS: We developed a new, agent based model that accounts for the essential in-host processes: parasite replication and its regulation by innate and adaptive immunity. The model also incorporates a simplified version of antigenic variation by Plasmodium falciparum. We calibrated the model using data from malaria-therapy (MT) studies, and developed a novel calibration procedure that accounts for a deterministic and a pseudo-random component in the observed parasite density patterns. Using the parasite density patterns of 122 MT patients, we generated a large number of calibrated parameters. The resulting data set served as a basis for constructing and simulating heterogeneous agent-based (AB) communities of MT-like hosts. We conducted several numerical experiments subjecting AB communities to realistic inoculation patterns reported from previous field studies, and compared the model output to the observed malaria prevalence in the field. There was overall consistency, supporting the potential of this agent-based methodology to represent transmission in realistic communities. CONCLUSIONS/SIGNIFICANCE: Our approach represents a novel, convenient and versatile method to model Plasmodium falciparum infection.

A sub-microscopic gametocyte reservoir can sustain malaria transmission.

BACKGROUND: Novel diagnostic tools, including PCR and high field gradient magnetic fractionation (HFGMF), have improved detection of asexual Plasmodium falciparum parasites and especially infectious gametocytes in human blood. These techniques indicate a significant number of people carry gametocyte densities that fall below the conventional threshold of detection achieved by standard light microscopy (LM). METHODOLOGY/PRINCIPAL FINDINGS: To determine how low-level gametocytemia may affect transmission in present large-scale efforts for P. falciparum control in endemic areas, we developed a refinement of the classical Ross-Macdonald model of malaria transmission by introducing multiple infective compartments to model the potential impact of highly prevalent, low gametocytaemic reservoirs in the population. Models were calibrated using field-based data and several numerical experiments were conducted to assess the effect of high and low gametocytemia on P. falciparum transmission and control. Special consideration was given to the impact of long-lasting insecticide-treated bed nets (LLIN), presently considered the most efficient way to prevent transmission, and particularly LLIN coverage similar to goals targeted by the Roll Back Malaria and Global Fund malaria control campaigns. Our analyses indicate that models which include only moderate-to-high gametocytemia (detectable by LM) predict finite eradication times after LLIN introduction. Models that include a low gametocytemia reservoir (requiring PCR or HFGMF detection) predict much more stable, persistent transmission. Our modeled outcomes result in significantly different estimates for the level and duration of control needed to achieve malaria elimination if submicroscopic gametocytes are included. CONCLUSIONS/SIGNIFICANCE: It will be very important to complement current methods of surveillance with enhanced diagnostic techniques to detect asexual parasites and gametocytes to more accurately plan, monitor and guide malaria control programs aimed at eliminating malaria.