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Background: Extreme weather is a recognised risk factor for stillbirth and preterm birth, disrupts women's access to healthcare during pregnancy and childbirth, and negatively affects the care of newborns. Reliable and accessible heat and weather warning systems are key in alerting individuals to undertake protective measures. There is a notable gap in understanding how women and caregivers in rural East Africa perceive and utilize weather information. We investigated community members' heat and weather warning information-seeking behaviour, identified available sources, assessed their reliability and utility, and examined their influence on behaviour., Settings: Our research was conducted in rural Kilifi County in Kenya's coastal region. The area experiences temperatures exceeding 23°C throughout the year, with extended periods of extreme temperatures [> 40°C] and long and severe droughts., Methods: We conducted in-depth interviews [IDI] with pregnant and postpartum women [n = 21] and held six focus group discussions [FGDs] involving mothers-in-law and community health volunteers [CHVs]. The data were analysed in NVivo 12 using both inductive and deductive approaches., Results: We found significant gaps concerning pregnant and post-partum women, and their caregivers, having timely access to weather forecasts and heat information from health or meteorological authorities. Information on heat and weather warnings is disseminated through various channels, including television, radio, mobile phones, and word of mouth, which are facilitated by community influencers such as CHVs and local chiefs. Indigenous methods of weather forecasting, such as cloud observation, consulting local "rainmakers", and studying the behavioural patterns of amphibians, are employed in conjunction with warnings from the Kenyan Meteorological Department (KMD). Barriers to accessing weather information include the cost of television and smartphones and a lack of segmented information in local languages., Conclusions: National and county meteorological services need to enhance public participation, communication, and the delivery of heat and weather information to guide community-level response measures and individual behaviour change. They should also collaborate with health professionals to address heat risks for vulnerable groups. Further research is needed to empower indigenous weather predictors with modern weather information and revise national policies to deliver tailored messages to vulnerable populations like pregnant and postpartum women., Competing Interests: The authors declare no competing interests., (Copyright: © 2024 Lusambili et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Malaria transmission across sub-Saharan Africa is sensitive to rainfall and temperature. Whilst different malaria modelling techniques and climate simulations have been used to predict malaria transmission risk, most of these studies use coarse-resolution climate models. In these models convection, atmospheric vertical motion driven by instability gradients and responsible for heavy rainfall, is parameterised. Over the past decade enhanced computational capabilities have enabled the simulation of high-resolution continental-scale climates with an explicit representation of convection. In this study we use two malaria models, the Liverpool Malaria Model (LMM) and Vector-Borne Disease Community Model of the International Centre for Theoretical Physics (VECTRI), to investigate the effect of explicitly representing convection on simulated malaria transmission. The concluded impact of explicitly representing convection on simulated malaria transmission depends on the chosen malaria model and local climatic conditions. For instance, in the East African highlands, cooler temperatures when explicitly representing convection decreases LMM-predicted malaria transmission risk by approximately 55%, but has a negligible effect in VECTRI simulations. Even though explicitly representing convection improves rainfall characteristics, concluding that explicit convection improves simulated malaria transmission depends on the chosen metric and malaria model. For example, whilst we conclude improvements of 45% and 23% in root mean squared differences of the annual-mean reproduction number and entomological inoculation rate for VECTRI and the LMM respectively, bias-correcting mean climate conditions minimises these improvements. The projected impact of anthropogenic climate change on malaria incidence is also sensitive to the chosen malaria model and representation of convection. The LMM is relatively insensitive to future changes in precipitation intensity, whilst VECTRI predicts increased risk across the Sahel due to enhanced rainfall. We postulate that VECTRI's enhanced sensitivity to precipitation changes compared to the LMM is due to the inclusion of surface hydrology. Future research should continue assessing the effect of high-resolution climate modelling in impact-based forecasting., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Talib et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)