Amelia Bertozzi-Villa

Since their rapid adoption from the mid 2000s, insecticide-treated nets (ITNs) have been one of the most ubiquitous and impactful malaria interventions in Africa. Facing insecticide resistance and ever-increasing resource constraints, there is a growing need to revise previous modelling efforts of ITN coverage to better reflect the current epidemiological reality. Comprehensive estimates of ITN coverage must account for factors such as net type, net age, and user behaviours. By leveraging improved data availability, we propose a mathematically rigorous and interpretable ITN coverage model that extends previous national-level ITN models to the subnational level across 44 countries in Africa. The presented Multitype-ITN (MITN) model is used to construct longitudinal estimates of net demography by age and type from 2006 to 2024, and provide insights on potential sources of ITN distribution inefficiencies. Our findings show a significant increase in the uptake of next-generation ITNs, and thus reflect an increasingly diverse market. However, longitudinal coverage suggests stagnation in key metrics of net ownership such as nets-per-capita, access and use, alongside a downwards trend in utilisation – number of users per net. Coupled with observed stationary levels of use rate – proportion of people with access that also use nets. There are also early signs of interventions failing to meet the demands of increasing populations. Our results provide more nuanced metrics of ITN coverage that account for factors such as type and age, which may inform the design of future net allocation policies.

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.