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Background: Malaria epidemics are increasing in East Africa since the 1980s, coincident with rising temperature and widening climate variability. A projected 1-3.5 °C rise in average global temperatures by 2100 could exacerbate the epidemics by modifying disease transmission thresholds. Future malaria scenarios for the Lake Victoria Basin (LVB) are quantified for projected climate scenarios spanning 2006-2100., Methods: Regression relationships are established between historical (1995-2010) clinical malaria and anaemia cases and rainfall and temperature for four East African malaria hotspots. The vector autoregressive moving average processes model, VARMAX (p,q,s), is then used to forecast malaria and anaemia responses to rainfall and temperatures projected with an ensemble of eight General Circulation Models (GCMs) for climate change scenarios defined by three Representative Concentration Pathways (RCPs 2.6, 4.5 and 8.5)., Results: Maximum temperatures in the long rainy (March-May) and dry (June-September) seasons will likely increase by over 2.0 °C by 2070, relative to 1971-2000, under RCPs 4.5 and 8.5. Minimum temperatures (June-September) will likely increase by over 1.5-3.0 °C under RCPs 2.6, 4.5 and 8.5. The short rains (OND) will likely increase more than the long rains (MAM) by the 2050s and 2070s under RCPs 4.5 and 8.5. Historical malaria cases are positively and linearly related to the 3-6-month running means of monthly rainfall and maximum temperature. Marked variation characterizes the patterns projected for each of the three scenarios across the eight General Circulation Models, reaffirming the importance of using an ensemble of models for projections., Conclusions: The short rains (OND), wet season (MAM) temperatures and clinical malaria cases will likely increase in the Lake Victoria Basin. Climate change adaptation and mitigation strategies, including malaria control interventions could reduce the projected epidemics and cases. Interventions should reduce emerging risks, human vulnerability and environmental suitability for malaria transmission., (© 2022. The Author(s).)

Background: There is concern in the international community regarding the influence of climate change on weather variables and seasonality that, in part, determine the rates of malaria. This study examined the role of sociodemographic variables in modifying the association between temperature and malaria in Kanungu District (Southwest Uganda)., Methods: Hospital admissions data from Bwindi Community Hospital were combined with meteorological satellite data from 2011 to 2014. Descriptive statistics were used to describe the distribution of malaria admissions by age, sex, and ethnicity (i.e. Bakiga and Indigenous Batwa). To examine how sociodemographic variables modified the association between temperature and malaria admissions, this study used negative binomial regression stratified by age, sex, and ethnicity, and negative binomial regression models that examined interactions between temperature and age, sex, and ethnicity., Results: Malaria admission incidence was 1.99 times greater among Batwa than Bakiga in hot temperature quartiles compared to cooler temperature quartiles, and that 6-12 year old children had a higher magnitude of association of malaria admissions with temperature compared to the reference category of 0-5 years old (IRR = 2.07 (1.40, 3.07))., Discussion: Results indicate that socio-demographic variables may modify the association between temperature and malaria. In some cases, such as age, the weather-malaria association in sub-populations with the highest incidence of malaria in standard models differed from those most sensitive to temperature as found in these stratified models., Conclusion: The effect modification approach used herein can be used to improve understanding of how changes in weather resulting from climate change might shift social gradients in health., (© 2022. The Author(s).)

We investigate the short-term effects of air temperature, rainfall, and socioeconomic indicators on malaria incidence across Rwanda and Uganda from 2002 to 2011. Delayed and nonlinear effects of temperature and rainfall data are estimated using generalised additive mixed models with a distributed lag nonlinear specification. A time series cross-validation algorithm is implemented to select the best subset of socioeconomic predictors and to define the degree of smoothing of the weather variables. Our findings show that trends in malaria incidence agree well with variations in both temperature and rainfall in both countries, although factors other than climate seem to play an important role too. The estimated short-term effects of air temperature and precipitation are nonlinear, in agreement with previous research and the ecology of the disease. These effects are robust to the effects of temporal correlation. The effects of socioeconomic data are difficult to ascertain and require further evaluation with longer time series. Climate-informed models had lower error estimates compared to models with no climatic information in 77 and 60% of the districts in Rwanda and Uganda, respectively. Our results highlight the importance of using climatic information in the analysis of malaria surveillance data, and show potential for the development of climate informed malaria early warning systems.

Although malnutrition and malaria co-occur among individuals and populations globally, effects of nutritional status on risk for parasitemia and clinical illness remain poorly understood. We investigated associations between Plasmodium falciparum infection, nutrition, and food security in a cross-sectional survey of 365 Batwa pygmies in Kanungu District, Uganda in January of 2013. We identified 4.1% parasite prevalence among individuals over 5 years old. Severe food insecurity was associated with increased risk for positive rapid immunochromatographic test outcome (adjusted relative risk [ARR] = 13.09; 95% confidence interval [95% CI] = 2.23-76.79). High age/sex-adjusted mid-upper arm circumference was associated with decreased risk for positive test among individuals who were not severely food-insecure (ARR = 0.37; 95% CI = 0.19-0.69). Within Batwa pygmy communities, where malnutrition and food insecurity are common, individuals who are particularly undernourished or severely food-insecure may have elevated risk for P. falciparum parasitemia. This finding may motivate integrated control of malaria and malnutrition in low-transmission settings.

Malaria forecasts from dynamical systems have never been attempted at the health district or local clinic catchment scale, and so their usefulness for public health preparedness and response at the local level is fundamentally unknown. A pilot preoperational forecasting system is introduced in which the European Centre for Medium Range Weather Forecasts ensemble prediction system and seasonal climate forecasts of temperature and rainfall are used to drive the uncalibrated dynamical malaria model VECTRI to predict anomalies in transmission intensity 4 months ahead. It is demonstrated that the system has statistically significant skill at a number of sentinel sites in Uganda with high‐quality data. Skill is also found at approximately 50% of the Ugandan health districts despite inherent uncertainties of unconfirmed health reports. A cost‐loss economic analysis at three example sentinel sites indicates that the forecast system can have a positive economic benefit across a broad range of intermediate cost‐loss ratios and frequency of transmission anomalies. We argue that such an analysis is a necessary first step in the attempt to translate climate‐driven malaria information to policy‐relevant decisions. Plain Language Summary: The malaria parasite and its mosquito vector are both weather sensitive, with temperature impacting development rates and mortality, and rainfall providing mosquito breeding sites. We take advantage of these effects to provide forecasts of malaria transmission intensity up to 4 months ahead, using a state‐of‐the‐art climate prediction system to drive a mathematical model of the parasite/vector cycle. The system is evaluated to have skill in Uganda at the district and local clinic scale, a first for subnational forecasts. We then perform an economic analysis to show at which range of decision entry points and anomalous transmission events the system has positive benefit, necessary for integration into decision‐making processes. Key Points: A climate‐driven malaria early warning system is skillful at the subnational scale in UgandaA cost‐loss economic analysis allows a user to determine for which interventions and event frequency the system has valueShort health data records and lack of high‐quality sites hamper early warning system evaluation and improvement [ABSTRACT FROM AUTHOR]

Vulnerability to the health impacts of climate change will be shaped by the existing burden of ill- health and is expected to be highest in poor and socio-economically marginalized populations. Sub-Saharan Africa, in particular, is considered a highly vulnerable region. This paper analyses the vulnerability and adaptive capacity of rural Bakiga communities in southwestern Uganda to climate-sensitive health risks. The objectives were threefold: i) identify key climate-sensitive, community-identified health priorities; ii) describe and characterize determinants of sensitivity to these health priorities at the individual, community and regional levels; and iii) assess the adaptive capacity of Bakiga. Data collection employed a combination of individual and key informant interviews, biographies, future storylines, and Photovoice. Three key health risks were identified by the study communities (malaria, food insecurity, and gastrointestinal illnesses) - all affected by local climatic and environmental conditions, livelihoods, land use changes, and socio-economic conditions. Adaptation within these communities is dependent on their capacity to reduce sensitivities to identified health challenges among the potential of increasing exposures. Crop diversification, reducing deforestation, expanding of livestock rearing, transfer of traditional knowledge, and access to affordable health services are among potential strategies identified. We demonstrate significant existing vulnerabilities to present day climate-related health risks and highlight the importance of non-climatic processes and local conditions in creating sensitivity to health risks. Our place-based understanding is useful to inform interventions or policies aimed to reduce exposure and sensitivity and support adaptive capacity as the conditions these communities face are consistent with many other sub-Saharan African countries. [ABSTRACT FROM AUTHOR]

Background: The indigenous Batwa of southwestern Uganda are among the most highly impoverished populations in Uganda, yet there is negligible research on the prevalence of malaria in this population. Plasmodium falciparum malaria parasitaemia prevalence was estimated in an indigenous Batwa and a non-indigenous neighbouring population, and an exploration of modifiable risk factors was carried out to identify potential entry points for intervention. Additionally, evidence of zooprophylaxis was assessed, hypothesizing that livestock ownership may play a role in malaria risk. Methods: Two cross-sectional surveys of Batwa and non-Batwa communities were carried out in Kanungu District, Uganda in July 2013 and April 2014 based on a census of adult Batwa and a two-stage systematic random sample of adult non-Batwa in ten Local Councils where Batwa settlements are located. A community-based questionnaire and antigen rapid diagnostic test for P. falciparum were carried out in the cross-sectional health surveys. A multivariable logistic regression model was built to identify risk factors associated with positive malaria diagnostic test. A subset analysis of livestock owners tested for zooprophylaxis. Results: Batwa experienced higher prevalence of malaria parasitaemia than non-Batwa (9.35 versus 4.45 %, respectively) with over twice the odds of infection (OR 2.21, 95 % CI 1.23-3.98). Extreme poverty (OR 1.96, 95 % CI 0.98-3.94) and having an iron sheet roof (OR 2.54, 95 % CI 0.96-6.72) increased the odds of infection in both Batwa and non-Batwa. Controlling for ethnicity, wealth, and bed net ownership, keeping animals inside the home at night decreased the odds of parasitaemia among livestock owners (OR 0.29, 95 % CI 0.09-0.94). Conclusion: A health disparity exists between indigenous Batwa and non-indigenous community members with Batwa having higher prevalence of malaria relative to non-Batwa. Poverty was associated with increased odds of malaria infection for both groups. Findings suggest that open eaves and gaps in housing materials associated with iron sheet roofing represent a modifiable risk factor for malaria, and may facilitate mosquito house entry; larger sample sizes will be required to confirm this finding. Evidence for possible zooprophylaxis was observed among livestock owners in this population for those who sheltered animals inside the home at night. [ABSTRACT FROM AUTHOR]

Major efforts for malaria prevention programs have gone into scaling up ownership and use of insecticidal mosquito nets, particularly in sub-Saharan Africa where the malaria burden is high. Socioeconomic inequities in access to long lasting insecticidal nets (LLINs) are reduced with free distributions of nets. However, the relationship between social factors and retention of nets after a free distribution has been less studied, particularly using a longitudinal approach. Our research aimed to estimate the ownership and use of LLINs, and examine the determinants of LLIN retention, within an Indigenous Batwa population after a free LLIN distribution. Two LLINs were given free of charge to each Batwa household in Kanungu District, Uganda in November 2012. Surveyors collected data on LLIN ownership and use through six cross-sectional surveys pre- and post-distribution. Household retention, within household access, and individual use of LLINs were assessed over an 18-month period. Socioeconomic determinants of household retention of LLINs post-distribution were modelled longitudinally using logistic regression with random effects. Direct house-to-house distribution of free LLINs did not result in sustainable increases in the ownership and use of LLINs. Three months post-distribution, only 73% of households owned at least one LLIN and this period also saw the greatest reduction in ownership compared to other study periods. Eighteen-months post distribution, only a third of households still owned a LLIN. Self-reported age-specific use of LLINs was generally higher for children under five, declined for children aged 6–12, and was highest for older adults aged over 35. In the model, household wealth was a significant predictor of LLIN retention, controlling for time and other variables. This research highlights on-going socioeconomic inequities in access to malaria prevention measures among the Batwa in southwestern Uganda, even after free distribution of LLINs, and provides critical information to inform local malaria programs on possible intervention entry-points to increase access and use among this marginalized population. [ABSTRACT FROM AUTHOR]

The ECMWF S2S (extended range ensemble prediction system, EPS) and seasonal forecast system are used in an integrated seamless prediction system to drive a dynamical malaria model in Africa, to produce malaria transmission anomaly predictions up to four months ahead. We show the potential skill of this system across Africa, and then evaluate the early warning system for malaria against district level and sentinel site health data for Uganda over the past 6 to 10 years and show that the system has skill in predicting transmission anomalies. This is the first ever demonstration of successful malaria health predictions on the sub-national scale using a fully dynamical prediction system. We show how a simple cost-loss economic analysis can help guide when to use an early warning system to guide health interventions, rather than simply always or never intervening. [ABSTRACT FROM AUTHOR]