Jaline Gerardin

Background: Mathematical modeling can be a useful approach to explore potential impact of malaria interventions and thereby inform resource prioritization decisions. However, expertise for applied modeling for public health decision-making is limited in malaria-endemic countries. A 4-month faculty enrichment program (FEP) in applied malaria modeling was implemented at Northwestern University, USA, in 2022 and 2023 with components including technical skills development, communication skills development, and domain knowledge on malaria epidemiology. Methods: Two cohorts of FEP participants and instructors were interviewed at baseline, midline, and endline to understand their expectations, experiences, and challenges with the program. Results: Participants valued their growth in technical expertise, research skills, and communication ability, as well as clear opportunities for knowledge transfer at their home institutions. Participants reported challenges with cross-disciplinary learning, balancing program components, and adapting to new teaching and learning styles. Instructors adapted program structures and teaching approaches to adjust to participant needs and reported strengthening of their own technical capacity. Conclusion: Training programs for technical skill development must be informed by the needs and priorities of prospective participants and include continuous feedback mechanisms to respond to emerging needs. Multi-pronged approaches increase long-term program value to participants and help establish pathways for knowledge transfer.

The extent to which insecticide-treated nets (ITNs), a key malaria prevention intervention in Sub-Saharan Africa, have been appropriately targeted to those at highest risk remains unknown, particularly within the urban context. We combined household surveys, programmatic ITN distribution data, and procurement cost data to estimate the number and cost of ITNs distributed in urban areas of Sub-Saharan Africa over the period 2010-2021, as well as trends in malaria prevalence and ITN access by wealth quintile. We estimate that over 440 million ITNs at a cost of over $1B USD have been distributed in urban areas, and allocations between rural and urban areas did not proportionately reflect the higher risk of malaria in rural areas. In urban areas, households in lower wealth quintiles were at higher risk of malaria but did not have greater access to ITNs. Housing quality and wealth but not ITN access or use were associated with decreased malaria prevalence in urban areas. If ITNs in urban areas had been distributed solely to slum residents, over $200 million could have been freed for other malaria control activities. In the context of needing to prioritize increasingly limited resources for health, ITN distributions must be better targeted to the most vulnerable.

In the context of high malaria burden and insufficient resources, several national malaria programs (NMPs) used subnational tailoring (SNT) as a tool for evidence-informed decision-making on their national malaria strategic plans and funding requests. SNT is a data-informed method of developing intervention plans that maximize health impact under limited resources across heterogenous areas and populations. The SNT process included the formation of an SNT team, determination of criteria for targeting interventions, data assembly and review, stratification, application of targeting criteria to determine preliminary plans, mathematical modeling, finalization of intervention plans, and monitoring and evaluation of the eventual implemented plan, all under the leadership of the NMP. Analysis steps of SNT were supported by the World Health Organization (WHO) and other partners. As SNT was a new approach, this study used semi-structured interviews to understand the perspectives and experiences of personnel from five NMPs (Burkina Faso, Ghana, Guinea, Nigeria, and Togo) that undertook SNT between 2019 and 2023. Participants reported that SNT outputs were used to inform national strategic plans and prioritized plans, that the process incentivized improvements in data collection and data quality, and that NMPs were strongly motivated to grow their capacity to conduct more steps of the SNT analysis process internally. Major challenges included the lack of resources available to implement the full strategic plans as well as challenges with data quality and alignment of stakeholders. Participants reported a moderate to strong sense of ownership over the process and were eager to extend, adapt, and reuse the SNT process in the future. Among countries supported by WHO, SNT was well-accepted and allowed NMPs to successfully use evidence to inform their decision-making, advocate for themselves, and mobilize resources.

Background Mathematical modeling can be a useful approach to explore potential impact of malaria interventions and thereby inform resource prioritization decisions. However, expertise for applied modeling for public health decision-making is limited in malaria-endemic countries. A 4-month faculty enrichment program (FEP) in applied malaria modeling was implemented at Northwestern University, USA, in 2022 and 2023 with components including technical skills development, communication skills development, and domain knowledge on malaria epidemiology. Methods Two cohorts of FEP participants and instructors were interviewed at baseline, midline, and endline to understand their expectations, experiences, and challenges with the program. Results Participants valued their growth in technical expertise, research skills, and communication ability, as well as clear opportunities for knowledge transfer at their home institutions. Participants reported challenges with cross-disciplinary learning, balancing program components, and adapting to new teaching and learning styles. Instructors adapted program structures and teaching approaches to adjust to participant needs and reported strengthening of their own technical capacity. Conclusion Training programs for technical skill development must be informed by the needs and priorities of prospective participants and include continuous feedback mechanisms to respond to emerging needs. Multi-pronged approaches increase long-term program value to participants and help establish pathways for knowledge transfer.

When models are used to inform decision-making, both their strengths and limitations must be considered. Using malaria as an example, we explain how and why models are limited and offer guidance for ensuring a model is well-suited for its intended purpose.

In the context of high malaria burden and insufficient resources, several national malaria programs (NMPs) used subnational tailoring (SNT) as a tool for evidence-informed decision-making on their national malaria strategic plans and funding requests. The SNT process included the formation of an SNT team, determination of criteria for targeting interventions, data assembly and review, stratification, application of targeting criteria to determine preliminary plans, mathematical modeling, finalization of intervention plans, and monitoring and evaluation of the eventual implemented plan, all under the leadership of the NMP. Analysis steps of SNT were supported by the World Health Organization (WHO) and other partners. As SNT was a new approach, this study used semi-structured interviews to understand the perspectives and experiences of personnel from five NMPs (Burkina Faso, Ghana, Guinea, Nigeria, and Togo) that undertook SNT between 2019 and 2023. Participants reported that SNT outputs were used to inform national strategic plans and prioritized plans, that the process incentivized improvements in data collection and data quality, and that NMPs were strongly motivated to grow their capacity to conduct more steps of the SNT analysis process internally. Major challenges included the lack of resources available to implement the full strategic plans as well as challenges with data quality and alignment of stakeholders. Participants reported a moderate to strong sense of ownership over the process and were eager to extend, adapt, and reuse the SNT process in the future. Among countries supported by WHO, SNT was well-accepted and allowed NMPs to successfully use evidence to inform their decision-making, advocate for themselves, and mobilize resources.

Background: In the context of high malaria burden yet limited resources, Guinea’s national malaria program adopted an innovative subnational tailoring (SNT) approach, including engagement of stakeholders, data review, and data analytics, to update their malaria operational plan for 2024-2026 and identify the most appropriate interventions for each district considering the resources available. Methods: Guinea’s malaria program triggered the SNT exercise with a list of decisions that could be informed with local data. The program established an SNT team, which determined intervention targeting criteria; identified, assembled, and reviewed relevant data sources; stratified malaria risk and its determinants to inform geographical targeting for each intervention; and used mathematical modeling to predict the impact of different intervention mix scenarios. The SNT analysis was performed at the district level, excluding the urban area of Conakry. Results: Malaria incidence, malaria prevalence, and all-cause under-5 mortality were used for the epidemiological stratification of Guinea. Additional indicators relevant for decisions-making including seasonality patterns, insecticide resistance or malaria interventions and vaccine coverage were also stratified. Stratified layers were used to inform the targeting criteria for each intervention to identify districts to prioritize for indoor residual spray, dual-action insecticide-treated nets, seasonal malaria chemoprevention (SMC) including number of cycles for each eligible district, malaria vaccine, and perennial malaria chemoprevention. Results of the SNT analysis were used to mobilize funding from the Global Fund for scale-up of dual-action nets and expansion of SMC. Conclusions: SNT allowed Guinea’s national malaria program to adapt their intervention strategy at the health district level, an unprecedented approach in the country. The use of local data to inform eligibility and prioritization allowed the program to identify the optimal mix of interventions for each district and to successfully mobilize resources to support their plans.

Urban population growth in Nigeria may exceed the availability of affordable housing and basic services, resulting in living conditions conducive to vector breeding and heterogeneous malaria transmission. Understanding the link between community-level factors and urban malaria transmission informs targeted interventions. We analyzed Demographic and Health Survey Program cluster-level data, alongside geospatial covariates, to describe variations in malaria prevalence in children under 5 years of age. Univariate and multivariable models explored the relationship between malaria test positivity rates at the cluster level and community-level factors. Generally, malaria test positivity rates in urban areas are low and declining. The factors that best predicted malaria test positivity rates within a multivariable model were post-primary education, wealth quintiles, population density, access to improved housing, child fever treatment-seeking, precipitation, and enhanced vegetation index. Malaria transmission in urban areas will likely be reduced by addressing socioeconomic and environmental factors that promote exposure to disease vectors. Enhanced regional surveillance systems in Nigeria can provide detailed data to further refine our understanding of these factors in relation to malaria transmission.

Background Decision-makers impose COVID-19 mitigations based on public health indicators such as reported cases, which are sensitive to fluctuations in supply and demand for diagnostic testing, and hospital admissions, which lag infections by up to two weeks. Imposing mitigations too early has unnecessary economic costs, while imposing too late leads to uncontrolled epidemics with unnecessary cases and deaths. Sentinel surveillance of recently-symptomatic individuals in outpatient testing sites may overcome biases and lags in conventional indicators, but the minimal outpatient sentinel surveillance system needed for reliable trend estimation remains unknown. Methods We used a stochastic, compartmental transmission model to evaluate the performance of various surveillance indicators at reliably triggering an alarm in response to, but not before, a step increase in transmission of SARS-CoV-2. The surveillance indicators included hospital admissions, hospital occupancy, and sentinel cases with varying levels of sampling effort capturing 5, 10, 20, 50 or 100% of incident mild cases. We tested 3 levels of transmission increase, 3 population sizes, and condition of either simultaneous transmission increase, or lagged increase in older population. We compared the indicators’ performance at triggering alarm soon after, but not prior, to the transmission increase. Results Compared to surveillance based on hospital admissions, outpatient sentinel surveillance that captured at least 20% of incident mild cases could trigger alarm 2 to 5 days earlier for a mild increase in transmission and 6 days earlier for moderate or strong increase. Sentinel surveillance triggered fewer false alarms and averted more deaths per day spent in mitigation. When transmission increase in older populations lagged increase in younger populations by 14 days, sentinel surveillance extended its lead time over hospital admissions by an additional 2 days. Conclusions Sentinel surveillance of mild symptomatic cases can provide more timely and reliable information on changes in transmission to inform decision-makers in an epidemic like COVID-19.

Public health indicators typically used for COVID-19 surveillance can be biased or lag changing community transmission patterns. In this study, we investigate whether sentinel surveillance of recently symptomatic individuals receiving outpatient diagnostic testing for SARS-CoV-2 could accurately assess the instantaneous reproductive number R(t) and provide early warning of changes in transmission. We use data from community-based diagnostic testing sites in the United States city of Chicago. Patients tested at community-based diagnostic testing sites between September 2020 and June 2021, and reporting symptom onset within four days preceding their test, formed the sentinel population. R(t) calculated from sentinel cases agreed well with R(t) from other indicators. Retrospectively, trends in sentinel cases did not precede trends in COVID-19 hospital admissions by any identifiable lead time. In deployment, sentinel surveillance held an operational recency advantage of nine days over hospital admissions. The promising performance of opportunistic sentinel surveillance suggests that deliberately designed outpatient sentinel surveillance would provide robust early warning of increasing transmission.