Peter W. Gething

Since their rapid adoption from the mid 2000s, insecticide-treated nets (ITNs) have been one of the most 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 ITN coverage model that extends previous national-level 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 2006-2024, and provide insights on potential sources of ITN distribution inefficiencies. Our findings show a significant increase in the uptake of next-generation ITNs, reflecting an increasingly diverse market. However, longitudinal trends suggests stagnation in key metrics of net coverage (nets-per-capita, access and use), alongside a downwards trend in utilisation – number of users per net, coupled with observed stationary use rates – proportion of people with access that also use nets. There are also early signs of interventions failing to meet the demands of increasing populations.

The implications of climate change for malaria eradication this century remain poorly resolved^1,2. Many studies focus on parasite and vector ecology in isolation, neglecting the interactions between climate, malaria control and the socioeconomic environment, including disruption from extreme weather^3,4. Here we integrate 25 years of African data on climate, malaria burden and control, socioeconomic factors, and extreme weather. Using a geotemporal model linked to an ensemble of climate projections under the Shared Socioeconomic Pathway 2-4.5 (SSP 2-4.5) scenario⁵, we estimate the future impact of climate change on malaria burden in Africa, including both ecological and disruptive effects. Our findings indicate that climate change could lead to 123 million (projection range 49.5 million to 203 million) additional malaria cases and 532,000 (195,000–912,000) additional deaths in Africa between 2024 and 2050 under current control levels. Contrary to the prevailing focus on ecological mechanisms, extreme weather events emerge as the primary driver of increased risk, accounting for 79% (50–94%) of additional cases and 93% (70–100%) of additional deaths. Most increases stem from intensification in existing endemic areas rather than range expansion, with significant regional variation in impact. These results highlight the urgent need for climate-resilient malaria control strategies and robust emergency response systems to safeguard progress towards malaria eradication.

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.

Insecticide treated nets (ITNs) represent one of the most cost-effective malaria control measures that is widely adopted today. The construction of mechanistic models to describe structural distribution, ownership and attrition of ITNs are crucial in order to quantify historical impact and burden, and perform predictive estimates of intervention impact. Compartmental stock and flow (SNF) models have been the traditional approach to modelling ITN inventories and have remained the most commonly employed approach owing to their simplicity and ease of implementation. However, insight into the mathematical justification for commonly adopted modelling decisions are sparse. The calibration of SNF to observed data is also challenging due as data across disparate sampling frequencies and sparsity need to be reconciled. In this paper, we present a mathematical analysis of compartmental SNF models from both a time series analysis and dynamical systems approach to provide more insight on their dynamical behaviours. Using a reduced form of an SNF model, we show its equivalence to a linear time invariant system and demonstrate the criticality of attrition functions in the design SNF models. Additionally, we propose an iterative adapted expectation-maximisation (EM) algorithm to address SNF calibration challenges arising from disparate sampling frequencies alongside a list of required assumptions. Statistical analyses to verify the validity of these assumptions are presented. To the demonstrate its application, the subsequent EM method is applied to collected delivery, distribution and household survey data across 44 countries spanning 24 years to provide robust and statistically rigorous estimates of net distribution and volumes. Results for numerical convergence and uniqueness of outputs are also given.

Background: Insecticide treated nets (ITNs) represent a key tool in reducing human vector contact for malaria control. However, increasing insecticide resistance of malaria vectors threatens the effectiveness of pyrethroid-only nets in reducing malaria risk. Next- generation nets, such as those with dual active ingredients, have been recommended for use in areas with high malaria burden and confirmed pyrethroid resistance. Here, we assessed the impact of the distribution of Interceptor ^® G2 (IG2) ITNs on malaria cases in the Western North region of Ghana distributed in 2021. Methods: We analysed monthly numbers of confirmed malaria cases reported by health facilities in the Western North Region from 2018 to 2023. To control for possible confounding effects of climatic conditions, monthly mean values of both modelled vector habitat suitability and temperature suitability for the periods were included. Bayesian Poisson regression time series models were developed to assess the immediate and sustained impact of IG2 ITNs on malaria case trends. Results: Malaria cases reduced by 30% [odds ratio: 0.70, 95% CrI (0.624, 0.778)] immediately after the distribution of IG2 ITNs in the Western North region. This effect was sustained at six months up to 30 months post-intervention, where cases were reduced by 26% [odds ratio: 0.74, (0.65, 0.75) and 40% [odds ratio: 0.598 (0.495, 0.722)], respectively. The intervention was also strongly associated with reductions in malaria cases in seven of the nine districts in the region, after controlling for climatic factors. Conclusion: This study demonstrates the effectiveness of dual active Interceptor ^® G2 ITNs in the Western North region, an area with confirmed pyrethroid resistance. These findings support the scale-up of these next-generation nets by National Malaria Programs and highlight the need for further research to explore the utility of these nets in other high- burden malaria areas with region-specific insecticide resistance profiles. Key messages: Malaria prevalence and incidence both decreased after deployment of IG2 ITNs in the Western North region of Ghana. Distribution of IG2 ITNs caused immediate and sustained impact on malaria case reduction. Dual-active ingredient insecticide-treated nets are effective in field settings and could be deployed at a large-scale.

Background: Malaria in urban areas is a growing concern in most sub-Saharan African countries. The growing threats of Anopheles stephensi and insecticide resistance magnify this concern and hamper elimination efforts. It is therefore imperative to identify areas, within urban settings, of high-risk of malaria to help better target interventions. Methods: In this study, we combined a set of environmental, climatic, and urban covariates with observed data from a malaria prevalence study and used geospatial methods to predict malaria risk in the Greater Accra Region of Ghana. Georeferenced data from 12,371 surveyed children aged between 6 months and 10 years were included in the analysis. Results: Predicted malaria prevalence in this age group ranged from 0 to 52%. Satellite-driven data on tasselled cap brightness, enhanced vegetation index and a combination of urban covariates were predictive of malaria prevalence in the study region. We produced a map that quantified the probability of malaria prevalence exceeding 10%. Conclusions: This map revealed areas within the districts earmarked for malaria elimination that have high malaria risk. This work is providing evidence for use by the National Malaria Elimination Program and District Health Managers in planning and deploying appropriate malaria control strategies. Summary box: What is already known?: Reduction in malaria incidence globally has stalled in the past few years. Malaria endemic countries are being encouraged to use local data to inform appropriate malaria control strategies. Malaria prevalence studies seldomly provide estimates below regional administrative levels. The availability of environmental, climatic, and socioeconomic factors as well as computational methods has enhanced predictive methods that quantifies the disproportionate variation of malaria risk between and within urban areas. What are the new findings?: Predictive maps of malaria at high spatial resolutions such as 100m allows for visualizing fine-scale heterogeneity of malaria in neighbourhoods. Inclusion of urban covariates in models predicting malaria risk in urbanized communities helps to account for socioeconomic disparities and their effect on malaria risk. What do the new findings imply?: Malaria control efforts needs to be guided by highly granular data. Systems to generate granular data on a continuous basis needs to be strengthen in malaria endemic countries, especially, to better inform deployment of appropriate interventions in resource constraint settings. This type of analysis provide information on which intervention is appropriate in a specified geographical area.

Background: Since its inception in 2005, the President’s Malaria Initiative (PMI) has played a major role in the reductions in malaria morbidity and mortality witnessed across Africa. With the status of PMI funding and operations currently uncertain, this study aimed to quantify the impact that a fully-functioning PMI would have on malaria cases and deaths in Africa during 2025. Methods: We combined detailed spatio-temporal information on planned 2025 PMI and non-PMI malaria commodity procurement and distribution in Africa with spatio-temporal Bayesian models of intervention coverage and Plasmodium falciparum transmission and burden in Africa. By comparing coverage scenarios with and without planned PMI contributions we estimated the number of malaria cases and deaths PMI would avert in 2025. Findings: We estimated that business-as-usual PMI contributions to vector control, seasonal chemoprevention, and routine malaria treatment in Africa would avert in 2025 13·6M (95% uncertainty interval 11·4M – 16·4M) malaria cases and 104,000 (69,000 – 161,000) deaths. This represents 11·3% (9·9 – 12·9%) and 37·5% (34·2 – 41·5%), respectively, of the total burden of malaria morbidity and mortality in PMI’s focus geographies across 27 African countries. These estimates do not account for the additional impact of PMI-supported provision of diagnostics or severe case management commodities, nor preventive treatment for pregnant women which would add further to the averted burden. Interpretation: PMI investment in supporting procurement and distribution of malaria control commodities would translate directly into millions of malaria cases averted and a hundred thousand lives saved across its focus geographies in Africa across 2025. Research in context: Evidence before this study: We searched PubMed on 25 February 2025 with the search term “President’s Malaria Initiative” AND (impact OR evaluation) AND (burden OR malaria cases OR malaria deaths). 102 results were returned, of which four directly addressed the question of PMI-attributable impact on malaria burden across all its focus geographies. One focussed solely on case-management and did not provide quantitative results ¹ . A study focussing on mortality found a strong association between PMI investment and declines in all-cause infant mortality ² . Another study used a generalised estimating equation approach to assess PMI’s impact, concluding a strong association between PMI spending and reductions in malaria burden ³ . A 2017 study used a mechanistic malaria model to estimate PMI’s historic contribution to reductions in malaria morbidity and mortality, with future projections to 2020 ⁴ . Added value of this study: In this study we synthesised the most up-to-date information of all-funder volumes of key malaria control interventions (ITN, IRS, ACT, SMC) with PMI data on planned volumes and spatial targeting of funding in 2025 to derive near-real-time projections of malaria control intervention coverage in Africa under two scenarios: a business-as-usual scenario in which PMI commodities procured and distributed as previously planned versus a ‘no-PMI’ scenario in which PMI funding and technical assistance is absent. These scenario-based estimates of coverage were propagated through an empirical geospatial malaria model, coupled to mechanistic models of clinical incidence, in order to estimate the number of malaria infections, clinical cases, and deaths PMI activities could expect to avert in Africa in 2025. Implications of all available evidence: PMI is a key contributor to malaria control efforts in Africa, and as such its impact on averting childhood mortality has been demonstrated repeatedly. Here, using empirically-derived estimates of malaria control impact, combined with detailed scenarios of intervention coverage with and without PMI support, we isolated the contemporary impact of PMI activities on malaria morbidity and mortality in Africa in 2025. Our findings suggest that PMI support is critical to maintaining suppression of malaria transmission in its focus geographies.

The implications of climate change for malaria eradication in the 21 ^st century remain poorly resolved. Many studies have focussed on parasite and vector ecology in isolation, neglecting the interactions between climate, malaria control, and the socioeconomic environment, including the disruptive impact of extreme weather. Here we integrate 25 years of data on climate, malaria burden, control interventions, socioeconomic factors, and extreme weather events in Africa. Using a geotemporal model linked to an ensemble of climate projections under the Shared Socioeconomic Pathway 2-4.5 (SSP 2-4.5) scenario, we estimate the future impact of climate change on malaria burden in Africa, accounting for both ecological and disruptive effects. Our findings suggest climate change could lead to 123 million (projection range 49.5 million - 203 million) additional malaria cases and 532,000 (195,000 - 912,000) additional deaths in Africa between 2024 and 2050 under current control levels. Contrary to the prevailing focus on ecological mechanisms, extreme weather events emerge as the primary driver of increased risk, accounting for 79% (50-94%) of additional cases and 93% (70%-100%) of additional deaths. Most increases are due to intensification in existing endemic areas rather than range expansion, with significant regional variation in impact. These results highlight the urgent need for climate-resilient malaria control strategies and robust emergency response systems to safeguard progress toward malaria eradication in Africa.

No studies have yet examined high-resolution shifts in the spatial patterns of human movement in Australia throughout 2020 and 2021, a period coincident with the repeated enactment and removal of varied governmental restrictions aimed at reducing community transmission of SARS-CoV-2. We compared overlapping timeseries of COVID-19 pandemic-related restrictions, epidemiological data on cases and vaccination rates, and high-resolution human movement data to characterize population-level responses to the pandemic in Australian cities. We found that restrictions on human movement and/or mandatory business closures reduced the average population-level weekly movement volumes in cities, as measured by aggregated travel time, by almost half. Of the movements that continued to occur, long movements reduced more dramatically than short movements, likely indicating that people stayed closer to home. We also found that the repeated lockdowns did not reduce their impact on human movement, but the effect of the restrictions on human movement waned as the duration of restrictions increased. Lastly, we found that after restrictions ceased, the subsequent surge in SARS-CoV-2 transmission coincided with a substantial, non-mandated drop in human movement volume. These findings have implications for public health policy makers when faced with anticipating responses to restrictions during future emergency situations.