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. 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.

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. In this study, we assess how the probability of eventually reaching elimination of transmission depends on the critical threshold used in transmission assessment surveys (TAS-es) to define whether transmission was successfully suppressed and triple-drug MDA can be stopped. This analysis focuses on treatment-naive Indian settings. We do this for a range of epidemiological and programmatic contexts, using the established LYMFASIM model for transmission and control of LF. Based on our simulations, a single TAS, one year after the last MDA round, provides limited predictive value of having achieved suppressed transmission, while a higher MDA coverage increases elimination probability, thus leading to a higher predictive value. Every additional TAS, conditional on previous TAS-es being passed with the same threshold, further improves the predictive value for low values of stop-MDA thresholds. An mf prevalence threshold of 0.5% corresponding to TAS-3 results in ≥95% predictive value even when the MDA coverage is relatively low.

Elimination of transmission of onchocerciasis (river blindness) with long-term ivermectin mass drug administration with or without vector control in sub-Saharan Africa: a systematic review and meta-analysis.

BACKGROUND: WHO has proposed elimination of transmission of onchocerciasis (river blindness) by 2030. More than 99% of cases of onchocerciasis are in sub-Saharan Africa. Vector control and mass drug administration of ivermectin have been the main interventions for many years, with varying success. We aimed to identify factors associated with elimination of onchocerciasis transmission in sub-Saharan Africa. METHODS: For this systematic review and meta-analysis we searched for published articles reporting epidemiological or entomological assessments of onchocerciasis transmission status in sub-Saharan Africa, with or without vector control. We searched MEDLINE, PubMed, Web of Science, Embase, Cochrane Central Register of Controlled Trials, African Index Medicus, and Google Scholar databases for all articles published from database inception to Aug 19, 2023, without language restrictions. The search terms used were "onchocerciasis" AND "ivermectin" AND "mass drug administration". The three inclusion criteria were (1) focus or foci located in Africa, (2) reporting of elimination of transmission or at least 10 years of ivermectin mass drug administration in the focus or foci, and (3) inclusion of at least one of the following assessments: microfilarial prevalence, nodule prevalence, Ov16 antibody seroprevalence, and blackfly infectivity prevalence. Epidemiological modelling studies and reviews were excluded. Four reviewers (NM, AJ, AM, and TNK) extracted data in duplicate from the full-text articles using a data extraction tool developed in Excel with columns recording the data of interest to be extracted, and a column where important comments for each study could be highlighted. We did not request any individual-level data from authors. Foci were classified as achieving elimination of transmission, being close to elimination of transmission, or with ongoing transmission. We used mixed-effects meta-regression models to identify factors associated with transmission status. This study is registered in PROSPERO, CRD42022338986. FINDINGS: Of 1525 articles screened after the removal of duplicates, 75 provided 282 records from 238 distinct foci in 19 (70%) of the 27 onchocerciasis-endemic countries in sub-Saharan Africa. Elimination of transmission was reported in 24 (9%) records, being close to elimination of transmission in 86 (30%) records, and ongoing transmission in 172 (61%) records. I2 was 83·3% (95% CI 79·7 to 86·3). Records reporting 10 or more years of continuous mass drug administration with 80% or more therapeutic coverage of the eligible population yielded significantly higher odds of achieving elimination of transmission (log-odds 8·5 [95% CI 3·5 to 13·5]) or elimination and being close to elimination of transmission (42·4 [18·7 to 66·1]) than those with no years achieving 80% coverage or more. Reporting 15-19 years of ivermectin mass drug administration (22·7 [17·2 to 28·2]) and biannual treatment (43·3 [27·2 to 59·3]) were positively associated with elimination and being close to elimination of transmission compared with less than 15 years and no biannual mass drug administration, respectively. Having had vector control without vector elimination (-42·8 [-59·1 to -26·5]) and baseline holoendemicity (-41·97 [-60·6 to -23·2]) were associated with increased risk of ongoing transmission compared with no vector control and hypoendemicity, respectively. Blackfly disappearance due to vector control or environmental change contributed to elimination of transmission. INTERPRETATION: Mass drug administration duration, frequency, and coverage; baseline endemicity; and vector elimination or disappearance are important determinants of elimination of onchocerciasis transmission in sub-Saharan Africa. Our findings underscore the importance of improving and sustaining high therapeutic coverage and increasing treatment frequency if countries are to achieve elimination of onchocerciasis transmission. FUNDING: The Bill & Melinda Gates Foundation and Neglected Tropical Diseases Modelling Consortium, UK Medical Research Council, and Global Health EDCTP3 Joint Undertaking. TRANSLATIONS: For the Swahili, French, Spanish and Portuguese translations of the abstract see Supplementary Materials section.

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. A single change to the rules in one repository can hinder updating a public dashboard reliant on data pulled from external sources. These concerns are particularly challenging at the international level, because policies on systems aimed at harmonizing health and related data are typically dictated by national governments to serve their individual needs. OBJECTIVE: In this paper, we introduce a comprehensive public health data platform, EpiGraphHub, that aims to provide a single interoperable repository for open health and related data. METHODS: The platform, curated by the international research community, allows secure local integration of sensitive data while facilitating the development of data-driven applications and reports for decision-makers. Its main components include centrally managed databases with fine-grained access control to data, fully automated and documented data collection and transformation, and a powerful web-based data exploration and visualization tool. RESULTS: EpiGraphHub is already being used for hosting a growing collection of open data sets and for automating epidemiological analyses based on them. The project has also released an open-source software library with the analytical methods used in the platform. CONCLUSIONS: The platform is fully open source and open to external users. It is in active development with the goal of maximizing its value for large-scale public health studies.

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. Given the urgency of the situation and the magnitude of work required, we recruited a worldwide network of field experts, academics and students in the areas of public health, data science and social science to support the effort. Most analyses were performed on a merged line list of COVID-19 cases using a reverse engineering model (line listing built using data extracted from national situation reports shared by countries with the Regional Office for Africa as per the IHR (2005) obligations). The data analysis platform The Renku Project ( https://renkulab.io ) provided secure data storage and permitted collaborative coding.Over a period of 6 months, 63 contributors from 32 nations (including 17 African countries) participated in the project. A total of 45 in-depth country-specific epidemiological reports and data quality reports were prepared for 28 countries. Spatial transmission and mortality risk indices were developed for 23 countries. Text and video-based training modules were developed to integrate and mentor new members. The team also began to develop EpiGraph Hub, a web application that automates the generation of reports similar to those we created, and includes more advanced data analyses features (e.g. mathematical models, geospatial analyses) to deliver real-time, actionable results to decision-makers.Within a short period, we implemented a global collaborative approach to health data management and analyses to advance national responses to health emergencies and outbreaks. The interdisciplinary team, the hands-on training and mentoring, and the participation of local researchers were key to the success of this initiative.

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. We described five indicators of early COVID-19 spread and severity for each country as of 29 November 2020: delay in detection of the first case, length of the early epidemic growth period, cumulative and peak attack rates and crude case fatality ratio (CFR). We tested the influence of 13 pre-pandemic and pandemic response predictor variables on the country-level variation in the spread and severity indicators using multivariate statistics and regression analysis. We found that wealthier African countries, with larger tourism industries and older populations, had higher peak (p<0.001) and cumulative (p<0.001) attack rates, and lower CFRs (p=0.021). More urbanised countries also had higher attack rates (p<0.001 for both indicators). Countries applying more stringent early control policies experienced greater delay in detection of the first case (p<0.001), but the initial propagation of the virus was slower in relatively wealthy, touristic African countries (p=0.023). Careful and early implementation of strict government policies were likely pivotal to delaying the initial phase of the pandemic, but did not have much impact on other indicators of spread and severity. An over-reliance on disruptive containment measures in more resource-limited contexts is neither effective nor sustainable. We thus urge decision-makers to prioritise the reduction of resource-based health disparities, and surveillance and response capacities in particular, to ensure global resilience against future threats to public health and economic stability.

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. Here, we analysed early CD4 cell count measurements reported from ∼340,000 infected heterosexual individuals (HET) and men-who-have-sex-with-men (MSM), across geographies, ethnicities and calendar years. The reduction in CD4 counts early in infection is reflective of the virulence of T/F strains. MSM and HET use predominant modes of transmission, namely, anal and penile-vaginal, with among the largest differences in the selection pressures at transmission across modes. Further, in most geographies, the groups show little inter-mixing, allowing for the differential selection bias to be sustained and amplified. We found that the early reduction in CD4 counts was consistently greater in HET than MSM (P<0.05). To account for inherent variations in baseline CD4 counts, we constructed a metric to quantify the extent of progression to AIDS as the ratio of the reduction in measured CD4 counts from baseline and the reduction associated with AIDS. We found that this progression corresponding to the early CD4 measurements was ∼68% for MSM and ∼87% for HET on average (P<10-4; Cohen's d, ds = 0.36), reflecting the more severe disease caused by T/F strains in HET than MSM at the population level. Interestingly, the set-point viral load was not different between the groups (ds<0.12), suggesting that MSM were more tolerant and not more resistant to their T/F strains than HET. This difference remained when we controlled for confounding factors using multivariable regression. We concluded that the different selection pressures at transmission have resulted in more virulent T/F strains in HET than MSM. These findings have implications for our understanding of HIV-1 pathogenesis, evolution, and epidemiology.

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. To understand variation in the course of the pandemic in these nations, we explored differences in their economic statuses, healthcare expenditures and facilities, age and sex distributions, leading health risk factors, densities of the overall and urban populations and the main industries in these countries. We also reviewed the non-pharmaceutical response measures implemented nationally. We found that the burden of SARS-CoV-2 infection was reduced by strict early limitations on movement and biased towards nations where detection capacity was higher, while the burden of severe COVID-19 was skewed towards countries that invested less in healthcare and those that had older populations and greater prevalence of key underlying health risk factors. These findings highlight the need for Africa's island nations to invest more in healthcare and in local testing capacity to reduce the need for reliance on border closures that have dire consequences for their economies.

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. RESULTS: A total of 1656 deaths (2.4% of total cases reported) were reported, with men accounting for 70.5% of total deaths. In SSA, women had a lower CFR than men (mean [Formula: see text] = -0.9%; 95% credible intervals (CIs) -1.1% to -0.6%). The mean CFR estimates increased with age, with the sex-specific CFR differences being significant among those aged 40 years or more (40-59 age group: mean [Formula: see text] = -0.7%; 95% CI -1.1% to -0.2%; 60+ years age group: mean [Formula: see text] = -3.9%; 95% CI -5.3% to -2.4%). At the country level, 7 of the 20 SSA countries reported significantly lower CFRs among women than men overall. Moreover, corresponding to the age-specific datasets, significantly lower CFRs in women than men were observed in the 60+ years age group in seven countries and 40-59 years age group in one country. CONCLUSIONS: Sex and age are important predictors of COVID-19 mortality globally. Countries should prioritise the collection and use of sex-disaggregated data so as to design public health interventions and ensure that policies promote a gender-sensitive public health response.

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. We also find that beneficial mutations can enhance the fixation probability of a nonmutator. Our analysis is relevant to an understanding of recent experiments in which a reduction in the mutation rates has been observed.

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. The mutator population undergoes deleterious mutations at constant, but at a much higher rate than that of the non-mutator. We find that antagonistic epistasis lowers the chances of mutation rate reduction, while synergistic epistasis enhances it. Below a critical value of epistasis, the fixation probability behaves non-monotonically with variation in the mutation rate of the background population. Moreover, the variation of this critical value of the epistasis parameter with the strength of the mutator is discussed in the appendix. For synergistic epistasis, when selection is varied, the fixation probability reduces overall, with damped oscillations.

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. Compensatory mutations in the mutator population are found to decrease the fixation probability of a nonmutator when the selection coefficient is large. But, surprisingly, the fixation probability changes nonmonotonically with increasing compensatory mutation rate when the selection is mild. Using these results for the fixation probability and a drift-barrier argument, we find a novel relationship between the mutation rates and the population size. We also discuss the time to fix the nonmutator in an adapted population of asexual mutators, and compare our results with experiments.