Improved Assessment of Community Infection Through Data Resampling Method.

Background: The conventional diagnostic for 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.

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.

High urban NO triggers a substantial chemical downward flux of ozone.

Nitrogen oxides (NO) play a central role in catalyzing tropospheric ozone formation. Nitrogen dioxide (NO) has recently reemerged as a key target for air pollution control measures, and observational evidence points toward a limited understanding of ozone in high-NO environments. A complete understanding of the mechanisms controlling the rapid atmospheric cycling between ozone (O)-nitric oxide (NO)-NO in high-NO regimes at the surface is therefore paramount but remains challenging because of competing dynamical and chemical effects.

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.

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.

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.

Application of Schistosomiasis Consortium for Operational Research and Evaluation Study Findings to Refine Predictive Modeling of and 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 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 and 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.

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.

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.

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.

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 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.

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.

A comparison of two mathematical models of the impact of mass drug administration on the transmission and control of schistosomiasis.

The predictions of two mathematical models describing the transmission dynamics of schistosome infection and the impact of mass drug administration are compared. The models differ in their description of the dynamics of the parasites within the host population and in their representation of the stages of the parasite lifecycle outside of the host. Key parameters are estimated from data collected in northern Mozambique from 2011 to 2015.

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).

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.

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.

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.

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.

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.

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.

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.

Modeling the effect of chronic schistosomiasis on childhood development and the potential for catch-up growth with different drug treatment strategies promoted for control of endemic schistosomiasis.

In areas endemic for schistosomiasis having limited healthcare, targeted drug treatment of school-age children is recommended for control of Schistosoma-associated morbidity. However, optimal timing, number, and frequency of treatments are not established. Because longitudinal studies of long-term impact of treatment are few, for current policy considerations we performed quantitative simulation (based on calibrated modeling of Schistosoma-associated disease formation) to project the impact of different school-age treatment regimens.

A new approach to modelling schistosomiasis transmission based on stratified worm burden.

Background/objective: Multiple factors affect schistosomiasis transmission in distributed meta-population systems including age, behaviour, and environment. The traditional approach to modelling macroparasite transmission often exploits the 'mean worm burden' (MWB) formulation for human hosts. However, typical worm distribution in humans is overdispersed, and classic models either ignore this characteristic or make ad hoc assumptions about its pattern (e.

Connectivity sustains disease transmission in environments with low potential for endemicity: modelling schistosomiasis with hydrologic and social connectivities.

Social interaction and physical interconnections between populations can influence the spread of parasites. The role that these pathways play in sustaining the transmission of parasitic diseases is unclear, although increasingly realistic metapopulation models are being used to study how diseases persist in connected environments. We use a mathematical model of schistosomiasis transmission for a distributed set of heterogeneous villages to show that the transport of parasites via social (host movement) and environmental (parasite larvae movement) pathways has consequences for parasite control, spread and persistence.

A stochastic model of immune-modulated malaria infection and disease in children.

We develop a simple three-state stochastic description of individual malaria infections that relates dynamics of disease and immune status to age and previous exposure, under different intensities of transmission. We apply the resulting individual-based community models to examine the effects of drug treatment and vaccination on the frequency and severity of disease in ensembles of children. The several broad qualitative similarities between our results and field observations include potential rebound effects following intervals of drug treatment.