Surface ozone (O3) pollution is known to have a detrimental effect on agriculture whilst rising carbon dioxide (CO2) concentrations are sometimes found to offer plants protection against O3 effects. Considering the important role of sugarcane (Saccharum spp. hybrids) as a major food crop in South Africa and its contribution to the national economy, the tolerance of this crop to O3 damage must be established. A pilot study using open-top chambers was conducted whereby two local commercial sugarcane cultivars (NCo376 and N31) were fumigated during the summer growth season to explore the effects of elevated O3 as well as the interacting effects of O3 and CO2 on various stress and crop quality indicators. Statistical significance of differences in treatment means was analysed by hierarchical linear modelling to account for variability between chamber and pots in explaining changes across individual plants. The results revealed a significant reduction in the number of dead leaves (senescing) for the N31 cultivar exposed to elevated O3 compared with the other treatments. There was also a statistically significant decrease in chlorophyll fluorescence (used to assess photosynthetic performance) in the O3-treated NCo376 plants. This pilot study shows limited effects of O3 fumigation on growth and physiology, with preliminary indications that sugarcane is less sensitive to O3 than other crops. An increase in O3 concentrations associated with future climate change is expected, which will have implications for cultivar selection as a possible adaptation strategy to reduce susceptibility of this crop to O3. Significance: This article adds to the existing literature on sugarcane and ozone (O3). We present a pilot study for two cultivars of sugarcane and explore interacting effects of O3 and carbon dioxide (CO2) on various stress and crop quality indicators. We employed a mixed effects model to account for variability between chamber and pots, a challenge when working with plants. This is the first time African sugarcane has been investigated and, although the findings show limited statistical effect of O3 and CO2, future studies can vary the conditions of this experiment to produce more data points for a dose-response function.

Epidemiological evidence on short-term air pollution effects in low- and middle-income countries is limited by incomplete health surveillance and fragmented monitoring. South Africa’s three Air Quality Priority Areas (Highveld, Vaal Triangle Airshed, and Waterberg–Bojanala) is examined for acute health risks under data-limited conditions.We estimated short-term associations between major ambient pollutants and cause-specific mortality and morbidity using a distributed lag framework adapted for sparse datasets.Weekly mortality counts (ICD-10 J00–J99, A15–A19) and monthly morbidity data (2005–2020) were linked to district-level air pollutants. Analyses included district-specific distributed lag non-linear models (DLNMs, lags 0–3 weeks), and distributed lag case-crossover (DL-CCO) for mortality.A 10 µg/m³ increase in PM2.5 was associated with a 19% rise in respiratory mortality in the Highveld (RR = 1.19, 95% CI: 1.09–1.30). NO₂ exposure in the Vaal Triangle showed a 12% increase in tuberculosis deaths (RR = 1.12, 95% CI: 1.05–1.19). DL-CCO models confirmed similar lag–response patterns.Adapted DLNM and DL-CCO methods can recover robust pollution–health associations despite sparse data, highlighting significant short-term risks from NO₂ and PM2.5 in South Africa’s Priority Areas.

Regularly updating repositories of air pollution impacts on health is essential for evidence-based policies, interventions, and progress monitoring. However, this is often time-consuming and labour-intensive. Automation can ensure up-to-date evidence; reduce retrieval, screening time, and costs; and make information accessible to non-academic stakeholders. This study investigated whether a machine learning approach can perform any stages of a traditional scoping review on the health impacts, policies, and interventions related to air pollution due to domestic waste burning. A traditional approach was conducted in parallel with machine learning methods enabling a comparison of the efficiency and quality of the partially automated approach against the manual review. Findings from the two approaches were compared and the final set of included articles were considered for (1) reported impacts of waste burning on health outcomes and (2) recommendations on solutions and interventions to prevent/reduce adverse effects on health from waste burning. We found a range of health impacts associated with waste burning, including low birth weight, hypertensive disorders of pregnancy, adverse respiratory outcomes like asthma and wheeze, cancer risk, and mortality. Few studies proposed solutions or evaluated the effectiveness of interventions. The ML approach showed a tendency towards false positives, which are preferable to false negatives (where relevant papers were excluded). Results showed that the model can conduct initial searches and decisions for the review. However, the articles included in the model should be screened manually for final acceptance. Therefore, we propose a hybrid approach be used until the automated model can be further refined.

ObjectiveTuberculosis (TB) is one of the most prevalent public health challenges, particularly in developing countries where poverty, lack of sanitation and improper housing exacerbate the spread of infectious diseases. This study aimed to determine the socio-demographic and environmental factors associated with TB infection among children in the Hhohho region of Eswatini.MethodsWe conducted a cross-sectional study among children under 15 years diagnosed with TB (2022–2023) in Eswatini's Hhohho region, identified through hospital records. Data were collected via a structured survey and medical record review to assess environmental and socio-demographic risk factors. A Social Vulnerability Index (SVI) was constructed using 13 binary indicators to quantify cumulative social and environmental disadvantage. Social Vulnerability Index (SVI) from the Centers for Disease Control and Prevention (CDC) was utilised to investigate whether higher vulnerability correlates with a greater prevalence of TB symptoms.ResultsA high proportion (64%) of children were socially vulnerable, indicating multidimensional disadvantage. Children who are socially vulnerable face a significantly higher burden of TB symptoms (94%) compared to their less vulnerable peers (78%). Thus, social disadvantage directly increases health risks in children. The Expanded SVI therefore serves as an important indicator of social determinants of TB risk in the study populationConclusionThese results strongly suggest a need for targeted public health interventions that prioritize children who are economically disadvantaged. There is an ever-increasing need for policies that address upstream social determinants such as poverty, overcrowding, and poor nutrition that heighten TB risk.

In many low- and middle-income countries, unreliable electricity supply has led to widespread reliance on petrol (gasoline) and diesel generators. The type of fuel influences both the quantity and composition of emissions, which contribute substantially to air pollution and pose significant health risks. Emissions from household generators, similar to diesel exhaust, contain volatile organic compounds and particulate matter linked to adverse outcomes, including cancer. This review synthesizes evidence on health impacts associated with domestic generator emissions in Africa and proposes mitigation recommendations. We searched PubMed and Google Scholar for English-language studies using combinations of terms related to backup generators, emissions, air pollution, human health, and households. Studies were included if they explicitly examined household generator use as the exposure of interest in relation to health outcomes. Nine articles met the inclusion criteria. Generator emissions were found to contain harmful pollutants such as nitrogen oxides (NOx), sulphur dioxide (SO₂), and fine particulate matter (PM₂.5 and PM₁₀), all associated with well-established health risks. Exposure was linked to respiratory and cardiovascular diseases and increased mortality. However, epidemiological evidence was limited, with only 2

Background: Global heating is associated with adverse health impacts necessitating the implementation of Heat Action Plans (HAPs) to protect communities. Gauteng in South Africa is the most populated province, housing three cities (i.e., Johannesburg, Ekurhuleni, and Pretoria) and 25% of the national population. Objective: Given rising temperatures and projected increases in heatwaves and hot days, we gathered literature and case studies to inform the development of a Gauteng HAP. Methods: We conducted a scoping review to inform baseline data on heat‑related health impacts for Gauteng and South Africa too, followed by a benchmarking exercise that aimed to identify international best practices that may inform Gauteng’s plan. Benchmarking was done using Maharashtra (India), Victoria (Australia), and Khyber Pakhtunkhwa (Pakistan). Findings: Thirty‑six studies were included in the review, with 13 including Gauteng data and all showing impacts of heat on human health. Most studies applied epidemiological time series linking meteorological exposure (temperature/heat indices) and/or air pollutants (e.g., PM2.5, PM10, NO2, and O3) with health outcomes; applied remote‑sensing, reanalysis, or station data for exposure assessment; and used regression or distributed lag models. The benchmarking exercise identified exemplars’ distinctive strengths: Victoria’s district thresholds keep activation simple and local—ideal for Gauteng’s heterogeneous microclimates across metros and townships. Maharashtra’s graded activation and clear departmental roles reduce ambiguity during multi‑day heatwaves and thereby would help to align Gauteng Health, Infrastructure, Social Development departments. Khyber Pakhtunkhwa’s cooling‑camp model shows practical, low‑cost interventions of a low‑ and middle‑income country that can be replicated at taxi ranks/clinics/malls during temperature peaks. Conclusions: Insights from the literature and international exemplars provide a strong evidence base and adaptable models to guide a context‑specific, multi‑sectoral HAP for Gauteng that enhances preparedness, coordination, and community protection in a warming South Africa.

Rainfall and temperature are key climatic indicators essential for monitoring climate variability and change. Understanding long-term trends in these parameters is crucial for evidence-based policy formulation, particularly in vulnerable regions. We examined rainfall and temperature trends in Eswatini over a 40-year period (1981-2020) using meteorological data from five physiographic regions. Trends in monthly, seasonal and annual rainfall, alongside minimum and maximum temperatures, were analysed using the Mann-Kendall test and Sen's slope estimator. The results reveal high interannual variability and shifting seasonal precipitation patterns, with an overall decline in annual rainfall. Statistically significant declines were noted in June and October, especially in the Lowveld and Highveld regions, whereas certain summer months (December to February) recorded increasing rainfall trends at some stations. Temperature analysis indicated significant warming trends in maximum temperature at four stations (Big Bend, Mbabane, Malkerns and Nhlangano), with increases in minimum temperature most evident in Mbabane and Big Bend. A cooling trend was observed at Mhlume in the Western Lowveld, highlighting geographic temperature variability. These findings align with regional studies that have reported increased climate variability across southern Africa. The results emphasise the urgency of implementing adaptive strategies, including improved water resource management and the development of early warning systems. This research provides a foundation for informed climate policy interventions in Eswatini. Significance: This study provides a detailed assessment of long-term rainfall and temperature trends in Eswatini based on meteorological station data from 1981 to 2020. The findings show a general decline in rainfall and rising temperatures, with important seasonal and geographical differences across the country's physiographic regions. These changes have implications for water availability, ecological function and the vulnerability of climate-sensitive ecosystems. By linking observed trends to broader regional patterns and known climate drivers such as the El Ni & ntilde;o-Southern Oscillation, the study offers a baseline for national climate planning and contributes to a better understanding of climate variability in southern Africa.

Malaria remains a major challenge globally and in Africa, where climate change is likely to increase its prevalence among communities with low adaptive capacity. The aim of this study was to determine the characteristics of malaria dependence on meteorological drivers, and project incidences and spread of this disease in five district municipalities in Limpopo province, South Africa. We used data from weekly epidemiological reports on hospital admissions in the five municipalities to derive associations with corresponding regional temperature, rainfall, and evapotranspiration. Wavelet transform spectral analysis was applied to identify time lags characteristic for malaria development. We presumed that all the wavelet power spectra (WTS) peaks that we found in our data are characteristic times connected to the periods of development, distribution, and survival of either mosquitoes, as disease vectors, or the pathogens they transmit, or are the periods needed for human incubation of the disease. In this way, we were able to propose a regression model for the number of admissions cases, and to provide critical values of temperature, rainfall, and evapotranspiration that initiate the spread of the disease. Disease projections for 2021-2050 and 2051-2080 were made using Representative Concentration Pathways (RCPs): RCP2.6 and RCP8.5.

This review synthesised evidence on associations between air pollution and respiratory morbidity in Africa. Following PRISMA guidelines, we systematically searched PubMed, ScienceDirect and Elicit for case-control studies published between 2015 and 2025. Thirteen studies from ten African countries reported pollutant levels far exceeding WHO guidelines. Indoor PM₂.₅ in biomass-using homes ranged from 96 to 177 µg/m³, and ambient PM₂.₅ reached 259 µg/m³. Nitrogen oxides were consistently associated with reduced lung function in children, while household air pollution increased risks of under-five mortality and low birthweight. Associations with acute respiratory infections varied across settings. Vulnerability was greatest among young children, those with airway hyperresponsiveness, and households with poor ventilation. Only three studies included temperature, and none examined heat–respiratory interactions. Across African case-control studies, particulate matter and household air pollution remain consistently linked to adverse respiratory outcomes, highlighting urgent needs for cleaner fuels, improved ventilation, and stronger evidence on combined pollution and heat exposures.

Air pollution is a significant risk factor for a wide range of adverse health outcomes globally. In Africa, the health burden is exacerbated by high levels of pollution, limited infrastructure, and restricted access to health care interventions and solutions. Data science presents a valuable opportunity to address these challenges through enhanced prediction, monitoring, and response strategies. This scoping review provides a comprehensive analysis of data science applications in air pollution and health research across Africa. We examine how data science approaches such as machine learning, geospatial analysis, and predictive modelling are being employed to strengthen climate change forecasting and guide public health interventions. By synthesizing evidence from diverse African contexts, this study highlights the transformative potential of data science to inform evidence-based, context-specific responses to air pollution and its health impacts on the continent.

Domestic fuel use contributes significantly to household air pollution levels and to the disease burden in low-income households in South Africa. The link between residential fuel stacking and switching, and respiratory health, mediated by household air pollution, remains underexplored, posing challenges to transition to cleaner fuels. This study identified socio-economic determinants of fuel use patterns in two low-income communities of KwaZamokuhle and eMzinoni in South Africa. It also examined the impacts of these patterns on household air pollution levels and respiratory health outcomes. Over half of households relied on dirty fuels across all needs. Average household PM2.5 levels exceeded national daily standards (40 mu g/m(3)). Education level and employment status were significant factors in determining fuel choice, with employed participants less likely to rely on dirty fuels. Town-specific characteristics also influenced household fuel use patterns. In terms of health, 9.5 % of participants had obstructive airways disease and 26.9 % tested positive for inhalant allergens. Heating fuels were strongest predictor of obstructive airways disease (>75 %) whereas cooking fuels were the main predictor of allergen sensitivity (similar to 75 %). The stepwise introduction of cleaner fuels predicted better respiratory health outcomes. The findings of this study suggest that even the partial adoption of cleaner fuels has health benefits and supports the formulation of context-specific mitigation efforts aiming to address negative health effects associated with household air pollution.

Africa is experiencing the impacts of climate change. While global epidemiological studies using traditional analytical methods to study the relations between climate change and health exist, studies using data science to tackle these topics are increasing. The aim of this study was to identify how data science is being used to understand climate change impacts on health in Africa. We carried out a scoping review to synthesize the evidence of data science applied to understand health outcomes associated with climate change in Africa. Among 100 included articles, several temporal and spatial analytical tools and models were applied to determine the relationships between climate change factors and health outcomes for morbidity and mortality. For example, early warning systems for malaria were the most studied adaptation intervention. Africa has a wealth of evidence for addressing the health impacts of climate change to inform solutions for Africa and other countries around the world.

Air pollution poses a significant health risk globally, particularly in Sub-Saharan Africa. While domestic fuel burning is a well-known source of air pollution, outdoor sources beyond an individual's control, such as largescale biomass burning, can also significantly impact on indoor air quality. In South Africa's Kruger National Park, controlled burns are conducted during the winter months for ecological reasons and to mitigate the risk of wildfires, but their impact on local air quality is underexplored, especially in low- and middle-income countries. As part of a broader study, we monitored indoor PM2.5 concentrations in a rural community in Agincourt, Mpumalanga province, South Africa, over two weeks using low-cost sensors in nine dwellings. Ambient (outdoor) PM2.5 levels were simultaneously measured with a Zephyr air quality sensor. On 9 July 2023, we observed a peak in indoor PM2.5 in all households, as well as a peak in ambient PM2.5. On this day, 24-h indoor concentrations averaged 50 mu g/m3 (range: 43-55 mu g/m3), exceeding national guidelines. Satellite imagery and aerosol index data identified smoke plumes originating from Kruger National Park two days earlier. Using meteorological data from nearby Hoedspruit Air Force Base and HYSPLIT back-trajectory analysis, we identified that a wind shift on 9 July transported the plume over the community, showing air masses passing over the park before reaching the study site. Communities in South Africa already face high pollution levels from industrial and anthropogenic sources. These findings emphasise the need to further investigate relationships between controlled burning and human exposure, in order to aid refinement of controlled biomass burning practices to limit exposure to harmful pollutants and highlight the importance of developing strategies to inform and protect vulnerable communities.

Background: Exposure to non-optimal temperatures is associated with adverse health outcomes. Low-income communities living in informal housing (colloquially called shacks) are vulnerable to the negative health outcomes associated with non-optimal temperatures given the characteristics of their dwellings. Objective: The study aimed to measure wintertime temperatures in shacks in Bekkersdal, West Rand District Municipality (South Africa). Methods: iButtons were installed in 10 shacks for 13 days to measure temperature at 10-min intervals. Ambient outdoor temperature data were collected for the same period as the dwelling temperature campaign from the nearest automatic weather station operated by the South African Weather Service. A questionnaire was administered to 127 shack residents to determine household socio-demographics (participant age/gender; number living in dwelling; and length of stay in dwelling) and dwelling characteristics (type of wall/floor; presence/absence of insulation; energy used for heating). Results: Indoor temperatures ranged between 3 degrees C-33 degrees C (mean: 13 degrees C, median 12 degrees C). Daily mean indoor temperatures for all shacks combined were below the World Health Organization threshold for minimum indoor temperature of 18 degrees C for 94 % of the study duration. Indoor temperature increased as outdoor temperatures increased and this association was statistically significant (R = 0.98, p < 0.001). The majority of shacks (n = 108, 85 %) were made from corrugated iron sheeting and had no insulation hence the strong correlation between indoor and outdoor temperatures. Conclusions: The poor insulation of shacks exposes residents to cold outdoor temperatures. Thus, people living in shacks are vulnerable to the adverse health effects associated with extreme cold. Guidance on how to create thermally efficient shacks with insulation is recommended as a temporary solution. However, the main goal should be to replace shacks with adequate formal, low-cost housing, which the government should provide.

Background Exposure to fine particulate matter (PM2.5) is linked to many adverse outcomes, including respiratory and cardiovascular diseases. South Africa's reliance on coal combustion has led to poor air quality. Indoor air pollution exacerbates health risks in low-income households, necessitating thorough assessment. In this study, a human health risk assessment (HHRA) provided an understanding of health risks posed by indoor and outdoor PM2.5 concentrations in rural and urban settings. Methods During two campaigns, PM2.5 concentrations were monitored indoors (low-cost sensors in households) and outdoors (Zephyr sensors). We employed the method of the US Environmental Protection Agency in 22 urban households and 22 rural households. Results During a cooler period, indoor PM2.5 concentrations in all households exceeded the World Health Organization (WHO) Air Quality Guidelines. In Soweto, the winter 24-h PM2.5 concentrations reached as high as 491.4 mu g/m(3) (Household 19), surpassing all the WHO guideline targets, with the highest at 75 mu g/m(3). Even with conditions of higher atmospheric dispersion and less solid fuel burning, almost half of rural households had Hazard Quotients (HQs) > 1. In both seasons in urban areas and winter in rural areas, HQ values consistently remained >1, signalling greater health risks. Indoor PM2.5 concentrations almost consistently exceeded outdoor reference limits in both rural and urban locations throughout the year, underscoring the additional pollution burden due to indoor solid fuel burning and personal smoking habits. One Agincourt household recorded a warm period 24-h peak PM2.5 concentration of 1054 mu g/m(3) indoors, far higher than any corresponding outdoor values. Conclusions There is an urgent need for interventions to mitigate indoor air pollution that presents significant health risks to household occupants. Reducing health risks associated with high PM2.5 concentrations require interventions to mitigate outdoor PM2.5 levels and solid fuel use indoors. (347 words)

Personal solar ultraviolet radiation (UVR) exposure has positive and negative impacts on human health. Excess solar UVR exposure can be avoided through safe sun practices such as using sun protection and avoiding unprotected outdoor exposure when solar UVR levels are high. The shadow rule indirectly determines the sun's altitude by observing the length of a person's shadow during the course of the day. When the shadow cast by the sun on a horizontal surface is shorter than the height of the person casting the shadow, the solar UVR intensity is high and is deemed to have more risk. The magnitude of this risk depends on factors such a skin type, sun protection used etc. The UV Index is a standardized measure to describe the intensity of solar UVR with respect to the human action spectrum for sunburn. It is frequently reported in weather forecasts aimed at the public. Here, we demonstrate the potential utility of the shadow rule and how it may be understood in relation to the UV Index in a subtropical southern hemisphere setting. Its use as a simple awareness tool for sun protection in locations where the UV Index is not made public has value in promoting sun exposure awareness and reducing personal exposure risk.

Africa is grappling with severe food security challenges driven by population growth, climate change, land degradation, water scarcity, and socio-economic factors such as poverty and inequality. Climate variability and extreme weather events, including droughts, floods, and heatwaves, are intensifying food insecurity by reducing agricultural productivity, water availability, and livelihoods. This study examines the projected threats to food security in Africa, focusing on changes in temperature, precipitation patterns, and the frequency of extreme weather events. Using an Exponential Growth Model, we estimated the population from 2020 to 2050 across Africa’s five sub-regions. The analysis assumes a 5% reduction in crop yields for every degree of warming above historical levels, with a minimum requirement of 225 kg of cereals per person per year. Climate change is a critical factor in Africa’s food systems, with an average temperature increase of approximately +0.3 °C per decade. By 2050, the total food required to meet the 2100-kilocalorie per adult equivalent per day will rise to 558.7 million tons annually, up from 438.3 million tons in 2020. We conclude that Africa’s current food systems are unsustainable, lacking resilience to climate shocks and relying heavily on rain-fed agriculture with inadequate infrastructure and technology. We call for a transformation in food systems through policy reform, technological and structural changes, solutions to land degradation, and proven methods of increasing crop yields that take the needs of communities into account.