Effect of indoor residual spraying on sandfly abundance and incidence of visceral leishmaniasis in India, 2016-22: an interrupted time-series analysis and modelling study.

Background: Efforts to eliminate visceral leishmaniasis in India mainly consist of early detection and treatment of cases and indoor residual spraying with insecticides to kill the phlebotomine sandfly Phlebotomus argentipes that transmits the causative Leishmania protozoa. In this modelling study, we aimed to estimate the effect of indoor residual spraying (IRS) on vector abundance and transmission of visceral leishmaniasis in India.

Methods: In this time-series analysis and modelling study, we assessed the effect of IRS on vector abundance by using indoor vector-abundance data (from 2016 to 2022) and IRS quality-assurance data (from 2017-20) from 50 villages in eight endemic blocks in India where IRS was implemented programmatically.

Predictive Value of Microfilariae-Based Stop-MDA Thresholds After Triple Drug Therapy With IDA Against Lymphatic Filariasis in Treatment-Naive Indian Settings.

Mass drug administration (MDA) of antifilarial drugs is the main strategy for the elimination of lymphatic filariasis (LF). Recent clinical trials indicated that the triple-drug therapy with ivermectin, diethylcarbamazine, and albendazole (IDA) is much more effective against LF than the widely used two-drug combinations (albendazole plus either ivermectin or diethylcarbamazine). For IDA-based MDA, the stop-MDA decision is made based on microfilariae (mf) prevalence in adults.

Accelerating Progress Towards the 2030 Neglected Tropical Diseases Targets: How Can Quantitative Modeling Support Programmatic Decisions?

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.

A Platform for Data-Centric, Continuous Epidemiological Analyses (EpiGraphHub): Descriptive Analysis.

Background: Guaranteeing durability, provenance, accessibility, and trust in open data sets can be challenging for researchers and organizations that rely on public repositories of data critical for epidemiology and other health analytics. The required data repositories are often difficult to locate and may require conversion to a standard data format. Data-hosting websites may also change or become unavailable without warning.

Leveraging human resources for outbreak analysis: lessons from an international collaboration to support the sub-Saharan African COVID-19 response.

Emerging infectious diseases are a growing threat in sub-Saharan African countries, but the human and technical capacity to quickly respond to outbreaks remains limited. Here, we describe the experience and lessons learned from a joint project with the WHO Regional Office for Africa (WHO AFRO) to support the sub-Saharan African COVID-19 response.In June 2020, WHO AFRO contracted a number of consultants to reinforce the COVID-19 response in member states by providing actionable epidemiological analysis.

An in-depth statistical analysis of the COVID-19 pandemic's initial spread in the WHO African region.

During the first wave of the COVID-19 pandemic, sub-Saharan African countries experienced comparatively lower rates of SARS-CoV-2 infections and related deaths than in other parts of the world, the reasons for which remain unclear. Yet, there was also considerable variation between countries. Here, we explored potential drivers of this variation among 46 of the 47 WHO African region Member States in a cross-sectional study.

COVID-19 pandemic in Africa's island nations during the first 9 months: a descriptive study of variation in patterns of infection, severe disease, and response measures.

The geographic and economic characteristics unique to island nations create a different set of conditions for, and responses to, the spread of a pandemic compared with those of mainland countries. Here, we aimed to describe the initial period of the COVID-19 pandemic, along with the potential conditions and responses affecting variation in the burden of infections and severe disease burden, across the six island nations of the WHO's Africa region: Cabo Verde, Comoros, Madagascar, Mauritius, São Tomé e Príncipe and Seychelles. We analysed the publicly available COVID-19 data on confirmed cases and deaths from the beginning of the pandemic through 29 November 2020.

Transmitted HIV-1 is more virulent in heterosexual individuals than men-who-have-sex-with-men.

Transmission bottlenecks introduce selection pressures on HIV-1 that vary with the mode of transmission. Recent studies on small cohorts have suggested that stronger selection pressures lead to fitter transmitted/founder (T/F) strains. Manifestations of this selection bias at the population level have remained elusive.

COVID-19 mortality in women and men in sub-Saharan Africa: a cross-sectional study.

Introduction: Since sex-based biological and gender factors influence COVID-19 mortality, we wanted to investigate the difference in mortality rates between women and men in sub-Saharan Africa (SSA).

Method: We included 69 580 cases of COVID-19, stratified by sex (men: n=43 071; women: n=26 509) and age (0-39 years: n=41 682; 40-59 years: n=20 757; 60+ years: n=7141), from 20 member nations of the WHO African region until 1 September 2020. We computed the SSA-specific and country-specific case fatality rates (CFRs) and sex-specific CFR differences across various age groups, using a Bayesian approach.

Fixation probability of a nonmutator in a large population of asexual mutators.

In an adapted population of mutators in which most mutations are deleterious, a nonmutator that lowers the mutation rate is under indirect selection and can sweep to fixation. Using a multitype branching process, we calculate the fixation probability of a rare nonmutator in a large population of asexual mutators. We show that when beneficial mutations are absent, the fixation probability is a nonmonotonic function of the mutation rate of the mutator: it first increases sublinearly and then decreases exponentially.

Role of epistasis on the fixation probability of a non-mutator in an adapted asexual population.

The mutation rate of a well adapted population is prone to reduction so as to have a lower mutational load. We aim to understand the role of epistatic interactions between the fitness affecting mutations in this process. Using a multitype branching process, the fixation probability of a single non-mutator emerging in a large asexual mutator population is analytically calculated here.

Fixation probability of rare nonmutator and evolution of mutation rates.

Although mutations drive the evolutionary process, the rates at which the mutations occur are themselves subject to evolutionary forces. Our purpose here is to understand the role of selection and random genetic drift in the evolution of mutation rates, and we address this question in asexual populations at mutation-selection equilibrium neglecting selective sweeps. Using a multitype branching process, we calculate the fixation probability of a rare nonmutator in a large asexual population of mutators and find that a nonmutator is more likely to fix when the deleterious mutation rate of the mutator population is high.