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Over the past decade, considerable progress has been made in the control, elimination, and eradication of neglected tropical diseases (NTDs). Despite these advances, most NTD programs have recently experienced important setbacks; for example, NTD interventions were some of the most frequently and severely impacted by service disruptions due to the coronavirus disease 2019 (COVID-19) pandemic. Mathematical modeling can help inform selection of interventions to meet the targets set out in the NTD road map 2021-2030, and such studies should prioritize questions that are relevant for decision-makers, especially those designing, implementing, and evaluating national and subnational programs. In September 2022, the World Health Organization hosted a stakeholder meeting to identify such priority modeling questions across a range of NTDs and to consider how modeling could inform local decision making. Here, we summarize the outputs of the meeting, highlight common themes in the questions being asked, and discuss how quantitative modeling can support programmatic decisions that may accelerate progress towards the 2030 targets.

BACKGROUND: Global interest in malaria elimination has prompted research on active test and treat (TaT) strategies. METHODS: A systematic review and meta-analysis were conducted to assess the effectiveness of TaT strategies to reduce malaria transmission. RESULTS: A total of 72 empirical research and 24 modelling studies were identified, mainly focused on proactive mass TaT (MTaT) and reactive case detection (RACD) in higher and lower transmission settings, respectively. Ten intervention studies compared MTaT to no MTaT and the evidence for impact on malaria incidence was weak. No intervention studies compared RACD to no RACD. Compared to passive case detection (PCD) alone, PCD + RACD using standard diagnostics increased infection detection 52.7% and 11.3% in low and very low transmission settings, respectively. Using molecular methods increased this detection of infections by 1.4- and 1.1-fold, respectively. CONCLUSION: Results suggest MTaT is not effective for reducing transmission. By increasing case detection, surveillance data provided by RACD may indirectly reduce transmission by informing coordinated responses of intervention targeting.

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.

BackgroundDespite great achievements by insecticide-treated nets (ITNs) and indoor residual spraying (IRS) in reducing malaria transmission, it is unlikely these tools will be sufficient to eliminate malaria transmission on their own in many settings today. Fortunately, field experiments indicate that there are many promising vector control interventions that can be used to complement ITNs and/or IRS by targeting a wide range of biological and environmental mosquito resources. The majority of these experiments were performed to test a single vector control intervention in isolation; however, there is growing evidence and consensus that effective vector control with the goal of malaria elimination will require a combination of interventions.Method and findingsWe have developed a model of mosquito population dynamic to describe the mosquito life and feeding cycles and to optimize the impact of vector control intervention combinations at suppressing mosquito populations. The model simulations were performed for the main three malaria vectors in sub-Saharan Africa, Anopheles gambiae s.s, An. arabiensis and An. funestus. We considered areas having low, moderate and high malaria transmission, corresponding to entomological inoculation rates of 10, 50 and 100 infective bites per person per year, respectively. In all settings, we considered baseline ITN coverage of 50% or 80% in addition to a range of other vector control tools to interrupt malaria transmission. The model was used to sweep through parameters space to select the best optimal intervention packages. Sample model simulations indicate that, starting with ITNs at a coverage of 50% (An. gambiae s.s. and An. funestus) or 80% (An. arabiensis) and adding interventions that do not require human participation (e.g. larviciding at 80% coverage, endectocide treated cattle at 50% coverage and attractive toxic sugar baits at 50% coverage) may be sufficient to suppress all the three species to an extent required to achieve local malaria elimination.ConclusionThe Vector Control Optimization Model (VCOM) is a computational tool to predict the impact of combined vector control interventions at the mosquito population level in a range of eco-epidemiological settings. The model predicts specific combinations of vector control tools to achieve local malaria elimination in a range of eco-epidemiological settings and can assist researchers and program decision-makers on the design of experimental or operational research to test vector control interventions. A corresponding graphical user interface is available for national malaria control programs and other end users.

Over the past decade, considerable progress has been made in the control, elimination, and eradication of neglected tropical diseases (NTDs). Despite these advances, most NTD programs have recently experienced important setbacks; for example, NTD interventions were some of the most frequently and severely impacted by service disruptions due to the coronavirus disease 2019 (COVID-19) pandemic. Mathematical modeling can help inform selection of interventions to meet the targets set out in the NTD road map 2021–2030, and such studies should prioritize questions that are relevant for decision-makers, especially those designing, implementing, and evaluating national and subnational programs. In September 2022, the World Health Organization hosted a stakeholder meeting to identify such priority modeling questions across a range of NTDs and to consider how modeling could inform local decision making. Here, we summarize the outputs of the meeting, highlight common themes in the questions being asked, and discuss how quantitative modeling can support programmatic decisions that may accelerate progress towards the 2030 targets. [ABSTRACT FROM AUTHOR]

Opisthorchis viverrini is a parasitic liver fluke contracted by consumption of raw fish, which affects over 10 million people in Southeast Asia despite sustained control efforts. Chronic infections are a risk factor for the often fatal bile duct cancer, cholangiocarcinoma. Previous modeling predicted rapid elimination of O. viverrini following yearly mass drug administration (MDA) campaigns. However, field data collected in affected populations shows persistence of infection, including heavy worm burden, after many years of repeated interventions. A plausible explanation for this observation is systematic adherence of individuals in health campaigns, such as MDA and education, with some individuals consistently missing treatment. We developed an agent-based model of O. viverrini which allows us to introduce various heterogeneities including systematic adherence to MDA and education campaigns at the individual level. We validate the agent-based model by comparing it to a previously published population-based model. We estimate the degree of systematic adherence to MDA and education campaigns indirectly, using epidemiological data collected in Lao PDR before and after 5 years of repeated MDA, education and sanitation improvement campaigns. We predict the impact of interventions deployed singly and in combination, with and without the estimated systematic adherence. We show how systematic adherence can substantially increase the time required to achieve reductions in worm burden. However, we predict that yearly MDA campaigns alone can result in a strong reduction of moderate and heavy worm burden, even under systematic adherence. We predict latrines and education campaigns to be particularly important for the reduction in overall prevalence, and therefore, ultimately, elimination. Our findings show how systematic adherence can explain the observed persistence of worm burden; while emphasizing the benefit of interventions for the entire population, even under systematic adherence. At the same time, the results highlight the substantial opportunity to further reduce worm burden if patterns of systematic adherence can be overcome. Author summary: Opisthorchis viverrini is a liver parasite contracted by consumption of raw fish which affects over 10 million people in Southeast Asia despite sustained control efforts, with heavy infections being a major risk factor for often fatal bile duct cancer. Efforts to reduce the worm burden in populations include education of individuals on the safe consumption of fish meals, improvement of sanitation to interrupt the parasitic life cycle and mass drug administration campaigns, where ideally all targeted individuals of a population receive a drug against the parasite without a prior test of whether they are infected. We present a new agent-based mathematical model of Opisthorchis viverrini transmission and control. This model allows us to include systematic adherence to interventions, which describes the pattern of some individuals consistently being missed by interventions aimed at an entire (sub-)population. Our findings show how systematic adherence can explain the observed persistence of worm burden, but how interventions can be greatly beneficial even for individuals that systematically miss treatment. At the same time, we show the substantial opportunity to further reduce worm burden if patterns of systematic adherence can be overcome. [ABSTRACT FROM AUTHOR]

We consider a Darwinian (evolutionary game theoretic) version of a standard susceptible-infectious SI model in which the resistance of the disease causing pathogen to a treatment that prevents death to infected individuals is subject to evolutionary adaptation. We determine the existence and stability of all equilibria, both disease-free and endemic, and use the results to determine conditions under which the treatment will succeed or fail. Of particular interest are conditions under which a successful treatment in the absence of resistance adaptation (i.e. one that leads to a stable disease-free equilibrium) will succeed or fail when pathogen resistance is adaptive. These conditions are determined by the relative breadths of treatment effectiveness and infection transmission rate distributions as functions of pathogen resistance. [ABSTRACT FROM AUTHOR]

Background: Survival and gonotrophic cycle duration are important determinants of the vectorial capacity of malaria vectors but there are a limited number of approaches to estimate these quantities from field data. Time-series of observations of mosquitoes at different stages in the life-cycle are under-used. Methods: Anopheles funestus mosquitoes were caught using various methods over a 7.6-year period in Furvela, Mozambique. Survival and oviposition cycle duration were estimated using (i) an existing time-series approach for analysing dissections of mosquitoes caught in light-traps, extended to allow for variability in the duration of the cycle; (ii) an established approach for estimating cycle duration from resting collection data; (iii) a novel time-series approach fitted to numbers and categories of mosquitoes caught in exit-traps. Results: Data were available from 7,396, 6,041 and 1,527 trap-nights for exit-traps, light-traps and resting collections respectively. Estimates of cycle duration varied considerably between the different methods. The estimated proportion of female mosquitoes surviving each day of 0.740 (95% credible interval [0.650-0.815]) derived from light-trap data was much lower than the estimated daily survival of male mosquitoes from the model fitted to exit-trap data (0.881, 95% credible interval [0.747-0.987]). There was no tendency for the oviposition cycle to become shorter at higher temperature while the odds of survival of females through the cycle was estimated to be multiplied by 1.021 for every degree of mean weekly temperature increase (95% credible interval [0.991-1.051]). There was negligible temperature dependence and little inter-annual variation in male survival. Discussion: The time-series approach fitted to the exit-traps suggests that male An. funestus have higher survival than do females, and that male survival was temperature independent and unaffected by the introduction of long-lasting insecticidal nets (LLINs). The patterns of temperature dependence in females are at variance with results of laboratory studies. Time series approaches have the advantage for estimating survival that they do not depend on representative sampling of mosquitoes over the whole year. However, the estimates of oviposition cycle duration were associated with considerable uncertainty, which appears to be due to variability between insects in the duration of the resting period, and the estimates based on exit-trap data are sensitive to assumptions about relative trapping efficiencies. [ABSTRACT FROM AUTHOR]