Climate change and malaria in Chiredzi District, Zimbabwe: emerging evidence and pathways towards malaria prevention

Abstract

Background

Climate change can influence malaria incidence directly and indirectly, impacting vector and parasite dynamics, along with socioeconomic factors influencing malaria risk. In Zimbabwe there is a paucity of research linking climate change, environmental factors, and malaria incidence, hindering coordinated efforts for malaria elimination. Accordingly, the aim of the study was to explore the link between climate change, environmental factors, and malaria incidences, from 2010 to 2022, in Chiredzi district, Zimbabwe.

Methods

A transdisciplinary approach was applied, combining quantitative weather data from weather stations, malaria incidence data and insights from focus group discussions which were used to glean people’s perceptions and knowledge of climate change and malaria in Chiredzi District. Participatory mapping showing hot spots of malaria incidence were also utilized. Statistical analysis in MATLAB was used to analyse the weather and malaria data and a P-value of 0.0479 was obtained which is deemed as statistically significant. ATLAS.ti was used to qualitatively analyse data from the focus group discussions.

Results

Key results from the study show evidence of climate change in Chiredzi district manifesting through an increase in rainfall, increase in temperature, change in seasons and extreme weather patterns. Furthermore, there is a positive relationship between changes in climate and an increase in malaria incidence. However, in some years the relation is negative, and this can be attributed to other factors. Similarly, malaria incidence is also related to other socioeconomic and environmental factors such as poverty and migration which are further exacerbated by climate change. Malaria incidence is also attributed to other environmental and socio-economic factors.

Conclusions

Further studies with extended datasets that span a longer period need to be carried out. Likewise forecasting malaria incidence based on current climate, environmental and socio-economic conditions is crucial for advocating transformative malaria prevention programs, emphasizing the importance of inclusive partnership and adaptation to a changing climate. New malaria prevention programs that consider the impact of a changing climate on malaria, local environmental and socio-economic factors are urgently needed.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12936-025-05624-y.

Background

The nexus between climate change and diseases such as malaria is an ongoing debate. Increasing temperatures and changing precipitation patterns [1] and more extreme weather are threatening human health and safety, food and water security and socio-economic development in Africa [2–10]. Increases in temperature and changes in rainfall patterns also significantly affect population health across Africa, for example malaria incidences [11]. Climate change can influence malaria incidence directly and indirectly, impacting vector and parasite dynamics, along with socioeconomic factors influencing malaria [12–14]. Malaria affects developing countries and low-income countries such as Zimbabwe more [15–18]. This may lead to the hampered progress in the attainment of Sustainable Development Goals (SDGs) goals particularly SDG number 3: Good Health and Well-being [19–23].

In Zimbabwe there is a paucity of research linking climate change (the increase in temperature, precipitation, and flooding), environmental factors and malaria incidences [24]. This hampers policy response and leads to uncoordinated and untargeted efforts in trying to eliminate ate malaria. Most studies on the link between climate change are national thereby negating local factors and knowledge. Furthermore, many studies on climate models and malaria are not suitable for planning specific practical and targeted approaches in eliminating malaria [12, 25]. Similarly, many studies on malaria risk and climate change in Zimbabwe are not transdisciplinary and exclude citizen science and local parameters [15, 24, 26–33]. The study is interdisciplinary where secondary data, citizen science and participatory mapping where combined to explore the link between climate change, environmental factors and malaria incidences. This approach is envisaged to lead to a better targeted approach leading to practical elimination of malaria in Chiredzi District, Masvingo Province in Zimbabwe. Our study has two main research objectives namely (1) utilize secondary data and citizen science to understand the link between climatic and environmental factors and malaria incidence in Chiredzi District, Zimbabwe and (2), develop a joint vision based on the obtained data to devise targeted pathways for eliminating malaria.

Methods

Study area

The selected study area is Chiredzi District in the South-eastern lowveld of Zimbabwe (Fig. 1). Chiredzi District is a malaria prone area due to the average warm temperatures, average maximum temperature of 27 °C [15, 24]. Since 2000 it has been affected by extreme events such as flooding also damage infrastructure such as roads, bridges, and health infrastructure such as clinics and hospitals [34]. This affects access to health which may often lead to increased mortality from malaria. Furthermore, Chiredzi is in the South-eastern lowveld of Zimbabwe a low-lying area with the lowest point in the country at the confluence of the Save and Runde Rivers. Likewise, the economy of Chiredzi District is dependent on the sugar cane industry and nature conservation [35, 36]. Sugar cane farms utilize canal irrigation which has been cited as a breeding ground for mosquitoes. Similarly labor migration in the sugarcane farms, poor housing conditions for labourers in the farms and the canal irrigation is often cited as driving malaria incidence and providing a breeding ground for mosquito vectors. There are national parks and conservancies where rivers such as the Save, Runde and Mwenezi rivers traverse through the Gonarezhou National Park, Save Conservancy and Malilangwe conservancy. There are pans, pools, vegetation and wetlands in the national park and conservancies which can be breeding grounds for mosquito vectors [37, 38].

Fig. 1.

Location of Chiredzi District in Zimbabwe

The population in Chiredzi District is 303 503 according to the 2022 census [39]. This is disaggregated to 146 503 males and 157 000 females and 71 885 households. The livelihoods of most people in Chiredzi district is rainfed agriculture for most small holder farmers [36]. Commercial sugarcane farming is the backbone of the economy often supported by satellite smallholder farmers. Likewise, tourism because of Gonarezhou National Park and nature conservancies also drives the economy of Chiredzi District.

Approach

A trans-disciplinary approach is applied to explore the link between climate change and malaria in Chiredzi District, Masvingo Province, Zimbabwe from 2000 to 2022. Exclusively disciplinary or ‘pure’ academic research approaches are insufficient to develop comprehensive, holistic solutions for complex real-world challenges such as comprehending the nexus between climate change and malaria. Over 20 years ago, the so called “Mode 2 Science” [40] and trans-disciplinarity [41] were introduced as new scientific models of knowledge production. This new paradigm refers to various equivalent epistemologies, i.e., ways of generating knowledge in practice, art, and science. It thus questions the primacy of science and demands democratization the production of knowledge. The focus of transdisciplinary research lies in dealing with complex questions of “real-world”, so-called “Wicked Problems” [42], the creative solution approaches [43] and the consideration of different types of knowledge (including science, practice, system-, target- and transformation knowledge). Regional and local actors are carriers of implicit/tacit knowledge on local/regional preferences, priorities, knowledge perspective and other issues that might play an important role [41]. Consequently, this study applies a transdisciplinary approach to tackle the nexus between climate change and malaria in Chiredzi district in Zimbabwe. Thus, a combination of quantitative weather data from weather stations, malaria incidence data and focus group discussions that gleaned people’s perceptions and knowledge on climate change and malaria in Chiredzi District and participatory mapping showing perceptions of malaria incidence was utilized.

Data collection

The data used in this study was obtained through secondary data and focus group discussions and participatory maps to satisfy the study objectives. The quantitative data on weather patterns from the year 2000–2022 was obtained from Buffalo Range Airport, Chiredzi, Meteorological Services Department of Zimbabwe. This dataset contained the monthly rainfall in millimetres, minimum and maximum temperature data measured in degrees Celsius. Likewise, data from Ministry of Health and Child Care on malaria incidence on 34 health facilities in Chiredzi District was obtained. The malaria dataset contained suspected and confirmed malaria cases from the year 2010–2022. The suspected cases where people who exhibit malaria symptoms while the confirmed cases are positive cases confirmed with laboratory tests. a rapid diagnostic test or blood slide test where blood samples are collected and tested in a laboratory. The dataset contains monthly malaria cases observed in public and private healthcare facilities collected through the health management information system [44]. Collecting the malaria data and climate dataset enabled us to comprehend if there is a relationship between malaria incidence and weather patterns. To augment the climate and malaria five focus group discussions to glean the people’s perception on climate change and malaria where conducted.

The focus group discussions were conducted in September 2023. Permission from the gatekeepers, namely the Chiredzi Rural District Ministry of Health and Child Care, as well as the traditional leadership in the area where the discussions were held. This was crucial to legitimizing the study and ensuring that policy and practice could be informed by research. Chiredzi district was divided into four zones: Sengwe, Sangwe, Matibi 2, and Chiredzi North, where one workshop each was held in each zone. The workshops took place at the following locations: Manjinji Pan Hall (Sengwe), south of Gonarezhou National Park; Muhlanguleni Community Hall (Sangwe), in the centre of Chiredzi District; Chitsa Primary School (Matibi 2), northeast of Gonarezhou National Park; and Mkwasine Country Club (Chiredzi North) (Fig. 2).

Fig. 2.

Workshop locations

Each focus group discussion had on average of 30 participants. A village health worker and ward councillor in each zone was identified who spread the message about the purpose of the focus group discussion via WhatsApp groups and word of mouth transmission. Village health workers are also trained in malaria testing and treating before referral to the clinic for more complicated cases. Hence it was sensible for them to select participants and be part of the workshop proceedings. The village health worker and ward councillor ensured that each village in their respective zones was represented. The procedure for the workshop was that the participants were first informed of the purpose of the workshop which was to glean their perceptions on three themes namely, (1) community’s comprehension of climate change and how it manifests in the district, (2) what factors cause malaria in the district? (3) what are the pathways and challenges towards malaria elimination? Accordingly, participants where split in three groups with each group focusing on one theme and each group will present their findings followed by an overall discussion with all participants. Lastly, the participants would create a participatory map of their zone showing malaria prevalence which was colour coded with red (high malaria incidence), yellow (moderate malaria incidence) and green (low malaria incidence). The focus group discussion lasted approximately 4 h each and following the transdisciplinary and citizen science approach it was explicitly explained that the purpose was to learn and facilitate the discussion, and this enabled better responses. Similarly, the focus group discussion was conducted in local languages namely Tsonga, Ndebele and Shona depending on the location. The facilitation team could facilitate the discussions in the local languages, and this enabled better response with more details and nuances. Likewise, local customs at each workshop were adhered to. For example, participants always requested starting with a prayer and to be addressed by their Headman at the beginning or end of the workshop. At the end of each focus group discussion, the participants were thanked for attending.

Ethical clearance form University of Johannesburg was obtained and adherence to ethical principles was maintained by informing the participants that the information is strictly confidential, anonymous and that the information is used for research and informing policy.

Data cleaning, analysis and visualization

The quantitative data on weather patterns and malaria incidence was analysed using MATLAB software. First, the data was cleaned and checked for consistency using Microsoft Excel. For instance, the 2023 malaria case data was incomplete and was therefore excluded. The weather data spanned from 2000 to 2022, while the malaria data spanned from 2010 to 2022. Both datasets were analyzed from 2010 to 2022 to establish the link between weather patterns and malaria incidence. To compensate for the absence of malaria data before 2010, use was made of ten key informants, including village health workers, nurses, and doctors, who provided their opinions on malaria trends before 2010. Trend and descriptive statistical analyses on the weather and malaria data was conducted and visualized in graphs. Analysis of weather data averages on a seasonal and yearly basis was also conducted as well as regression analysis to model the relationship between rainfall and maximum and minimum temperature for each season. Similarly, correlation analysis between malaria incidence and weather data was done to determine the relationship between malaria and changes in weather phenomena. The p-value for the analysed data was 0.0479. (The statistical tests and seasonal analysis of weather data is in supplementary material). Data from the focus group discussions was written on flipcharts in local languages. This data was then translated into English and recorded in a Microsoft Word document. In some cases, workshop participants translated from the local languages into English during the workshop. The workshop data was then coded and analysed using ATLAS.ti software. This software enabled us to group the data into themes, which helped us understand how the community defines climate change and how it manifests in the district. It also helped us comprehend the factors causing malaria, as well as the pathways and challenges to eliminating malaria. The maps drawn by the participants helped us visualize how malaria manifests and is distributed within each zone.

Results and discussion

Changes in weather patterns

Figure 3 shows the change in average weather patterns in annual cumulative rainfall, from 2010 to 2020. From 2010 to 2016, average annual rainfall in Chiredzi district was less than 20 mm, increasing significantly to 140 mm in 2017 and 200 mm in 2020. Overall, there is an increase in annual rainfall from 2017 onwards which is six times more than the rainfall from 2010 to 2016. This shows significant change in rainfall variation which can be attributed to climate change. The increase in rainfall is conducive to breeding malaria causing mosquito vectors. Likewise, Chiredzi district has experienced an increase in the frequency and intensity of extreme storms such as the devastating cyclone Eline of 2000 which destroyed infrastructure such as bridges which denied communities access to healthcare facilities.

Fig. 3.

Changes in rainfall patterns in Chiredzi District from 2010 to 2020

Figure 4 shows that there has been an increase in the average temperature from 2010 to 2022) from 2010 to 2022.

Fig. 4.

Changes in average temperature in Chiredzi District from 2010 to 2022

Average maximum temperature was 34 °C in 2010 and increased to 35 °C in 2019. An increase in temperature has often been cited to increase the suitability of mosquito vectors to breed and expanding the spatial distribution of malaria causing mosquito vectors. Thus, from a climatic perspective there has been an increase in average monthly rainfall and temperature which are also increasing the risk of more breeding of the malaria causing mosquito vector [15].

Similarly, Fig. 5 shows change in seasonal changes of the weather parameters. The summer, spring and winter rainfall patterns show great variations while temperature shows less dramatic changes in the various seasons. The seasonal changes are further explained in supplementary material.

Fig. 5.

Seasonal changes in rainfall and temperature

Trends in malaria incidence and correlation with weather patterns

Figure 6 shows the trend in malaria incidence from 2010 to 2022 in Chiredzi District. Malaria cases in Chiredzi district shows an overall upward trend from 2010 to 2017 and a declining trend from 2018 to 2022. Significant increases in confirmed cases are in 2014 (26 613 cases), 2017 (35 548 cases) and 2018 (26 678 cases). In 2019 the malaria cases decreased by over 50% to 11 415 cases followed by an increase in 2020 and declines in 2021 and 2022.

Fig. 6.

Trends in malaria incidence from 2010 to 2022 in Chiredzi District

The relationship between malaria incidence and climate change requires evidence. In 2014 there was an increase in malaria cases accompanied by an increase in average maximum temperature from 2013 to 2014 (Fig. 6). Similarity malaria incidence peak in 2017 which is also accompanied by an increase in average maximum temperature from 2016 to 2018. This evidence provides a link between climate change and malaria, however in other years it is not very clear. For example, in 2019 malaria incidence decline although there is an increase in maximum temperature. This may be due to the success of preventive programmes to reduce the spread of malaria, thus more investigations into preventative programmes and malaria incidence are needed.

From a rainfall perspective, rainfall increases sharply from 2016 to 2018 accompanied by an increase in malaria incidence which shows a strong relationship between an increase in rainfall and malaria cases (Fig. 7). This is possible because an increase in rainfall provides more breeding grounds for mosquito as there are more water bodies. Furthermore, during the same period there is an average increase in temperature which further enables breeding of mosquito vectors. Rainfall declines in 2019 followed by a decline in malaria cases in the same year, whereas in 2020 rainfall increase and followed by an increase in malaria cases. Thus, there is a strong relationship between rainfall and malaria cases, and this is further supported by the generally average warmer temperatures of 30 °C. From 2020 rainfall continues to increase accompanied by a decline in malaria cases, this is attributed to the introduction of non-chemical-based innovations for malaria control borne out of the realization that there is a growing evidence of resistance to chemical-based malaria vector interventions [45].

Fig. 7.

Relation between temperature and malaria incidence in Chiredzi between 2010 and 2022

People’s knowledge and perceptions

Climate change and malaria

The respondents in the focus groups highlighted that the climate in Chiredzi district has changed as they have noticed that the seasons have changed. The participants expressed concern over the increase in summer temperatures over the past fifty years and this has resulted in more drier summers. With the drier season getting longer this means there are shorter periods of rainfall which has negatively affected their agricultural livelihood. During the same period participants noted that rainfall is now characterized often short heavy rainfall downpours which they attributed to a changing climate. The focus group participants noted that, because of the prolonged dry season, the earth becomes more drier and compact such that when there is rainfall there is poor filtration which results in formation of pools of stagnant water which results in more breeding grounds for malaria carrying mosquito vector mosquitoes. It was also mentioned that the increased temperatures make it even more suitable for malaria breeding vectors. Furthermore, another issue that has been noted is that due to this increase in temperature the winter seasons (May, June, July, and August) are not as cold anymore which means that people still get malaria in what is supposed to be winter as opposed to previous years where there were relatively little to no malaria cases during the winter season. Remarkably, it was mentioned that the months of September to October generally signal the start of the summer season but of late it has not been the case since during the September and October months cold spells have become common. Because winter seasons are not as cold anymore it has implied that malaria is no longer confined to the summer seasons. It is now not uncommon for malaria cases to the spread throughout the year unlike over 50 years ago where the participants argued that due to cold winters malaria cases would be negligible and most prevalent during the months of summer months of November and December which had high rainfall and temperature. The change is seasonal patterns to the rainfall and temperature are also confirmed by the statistical analysis (Fig. 5) particularly during summer, spring and winter. The change in seasons has affected farming and harvesting time where, as such due to shortage of rain during the summer season irrigation has been put in place to assist in crop production. These irrigation techniques particularly canal irrigation has become a breeding area for malaria vectors (Fig. 8).

Fig. 8.

The relationship between rainfall patterns and malaria incidence

Participants also mentioned that there are more strong winds and whirlwinds unlike the past 50 years. Thus, they argued that the strong winds and whirlwinds carry mosquito vectors as a result malaria has now spread spatially to locations where it was not very common in the district even though conditions there are not favorable to the breeding and existence of malaria vectors. They mentioned that in the past they used to experience winds that resulted in rainfall and these winds were south easterly. However, at present there are strong north easterly winds that bring little rainfall thereby extending the dry seasons and periods. However, the onset of the rainy season is now normally characterized by the heavy downpours which creates water puddles and water puddles which is a breeding ground for mosquitoes. Other notable changes are that the communities now experience periodic cloud cover with some unpredictable rainfall. They also reported that the weather becomes misty in summer especially in September, the things which never happened some years ago.

Factors causing malaria

Firstly, the participants concurred that malaria is caused by the anopheles’ mosquitoes which spreads malaria through biting a human being. Participants identified vegetation especially tall grass in and around the homesteads which attracts malaria causing mosquitoes. Another major factor causing an increase in malaria is stagnant water pools, wells, and gulley’s near homesteads where mosquito larvae breed. Unfortunately, when the community members go fetch water for household use in the wells, they expose themselves to mosquito bites. Related to this is the fact that Chiredzi district is traversed by major rivers such as Save, Mwenezi, Runde rivers and wetlands, such as the Manjinji pan south of Gonarezhou National Park which also act as breeding grounds for mosquito larvae. Unfortunately, some homesteads and communities live next to the rivers and wetlands. For example, communities next to Malipati business center where there are rivers and wetlands explained that their villages are malaria hotspots due to living close to water bodies. This is further exacerbated by inadequate pest control methods. For example, the absence of mosquito nets in some households and inadequate insecticide spraying interventions to control and eliminate. malaria vectors. Due to climate change the participants argue that insecticide spraying programs are not effective. For example, since seasons have shifted the spraying programmes still spray using the timeframes they did when the programmes started. For example, the onset of the rainy season and summer season have shifted but the spraying initiatives still spray during the same period it was thirty years ago, rendering control of mosquitoes ineffective.

Inadequate and mismanaged mosquito insecticide spraying programmes has exacerbated malaria incidence. For example, during the workshops the participants argued that the personnel in charge of spraying does not dilute the insecticide appropriately which renders the control programmes ineffective. Similarly, there are allegations that the insecticides are inappropriately diverted elsewhere which renders control programmes ineffective. Likewise, the participants also argue that some health facilities are not fully equipped with medication hence are unable to treat all malaria cases reported. This is further aggravated by poverty where the community members are not able to buy malaria medication for themselves. Due to poverty some community members when provided with mosquito nets to control mosquitoes use them to catch fish for selling to sustain their livelihoods. Thus, they become vulnerable as they are no longer protected from malaria causing vectors. Poverty is also linked to improper sanitation which was also cited as a leading cause supporting the breeding of mosquitoes. Communities revealed that they mostly use pit latrines as toilets and these pit latrines are fertile grounds for breeding mosquitoes. This is aggravated by by-laws that do not allow praying of mosquito insecticides in pit latrines.

A major driver of malaria is the sugarcane farming in Chiredzi District that utilizes canal irrigation. The canals can be breeding grounds for malaria causing vectors while population migration into crowded compounds during the peak sugarcane season is a major concern that drives malaria incidence. The sugarcane fields also attract malaria vectors and key informants, and participants highlighted that certain mosquito insecticide cannot be sprayed on canals and sugarcane fields as these affect the quality of the sugarcane crop. To aggravate the situation the situation in sugarcane farms that were allocated to the local smallholder farmers from the commercial farmers in 2000 during the Fast Track Land Reform [46, 47]. Participants argued that smallholder farmers are not maintaining their individual canals which end up being stagnant become a breeding ground for malaria causing vectors. Furthermore, it was mentioned that there is no collective effort by smallholder farmers to maintain and manage their canals which hampers malaria vector control. Likewise, participants mentioned that there is lack of cooperation between sugarcane small holder farmers, the rural district council and Ministry of Health and Childcare in controlling malaria vectors which leads to poor and ineffective vector control programmes.

Pathways towards malaria elimination

From the focus group discussion, it emerged that the communities knew substantially how they can control malaria. Firstly, they argued that proper hygiene such as cutting grass and covering household waste pits is crucial in reducing breeding ground of mosquito larvae. Furthermore, covering or closing wells that have stagnant water and putting oil in water puddle can effectively control breading mosquitoes. Nevertheless, there were concerns with using oil since it has negative downstream environmental impacts.

The participants also suggested that insecticide spraying programmes should be conducted based on new data on the new shifting seasons where mosquitoes breed unlike basing on past seasons. Communities also raised concerns about the labour-intensive nature of insecticide spraying where they are required to move their household furniture outside their houses. Thus, some households are hesitant, lock their compounds and or openly inform the personnel involved not to spray their houses. Additionally, the distribution and use of mosquito nets should be mandatory and supported by government agencies since not all community members can afford to purchase them given the high poverty levels. Moving towards proper sanitation where waste closets with flushing systems are utilized instead of pit latrines can aid in reducing malaria causing mosquito vectors.

Due to climate change participants suggested that mosquito nets should be used throughout the year and that programs for spraying mosquito insecticides should carried out through the year to prevent the breeding of malaria causing vectors. Furthermore, community members suggested cooperation, and coordination amongst various government agencies and Non-Governmental Organizations in the control of mosquitoes. Communities also encouraged aggressive education and awareness campaigns as a means of informing communities on how to prevent malaria.

Participants also suggested indigenous and traditional techniques of preventing malaria. For example, they informed us that burning maize cobs, cow dung, elephant dung, and a tree called Phungusuna in Tsonga are some of the various ways that they prevent malaria vectors from biting them. Community members also suggested use of mosquito repellent herbs, which they call in Tsonga punganyunyu, mutovhoti or tsombori. Another one was ingesting a climber tree’s fruit (kaka in Tsonga) which is tough to help in the production of bile in the pancreases and thus less likelihood of getting severely sick if you get malaria.

Malaria hot spots based on participatory GIS mapping

Figure 9 shows the participatory maps developed at Malipati and Mahlanguleni community. From the images the Malipati and Mahlanguleni residents argue that their area is a malaria hotspot as it is sandwiched between rivers and wetlands and proximity to Gonarezhou National Park which often has dense vegetation which are a fertile ground for breeding malaria vectors. Coupled with the persistent warm temperatures the community argued that their areas are malaria hotspots. Meanwhile Fig. 10 shows the perception of the Chitsa community on malaria hotspots in their community. The hotspots with red dots are mostly close to rivers and Gonarezhou National Park as well as in villages that have a relatively high population, such as at Ndali in the south. They also argue that the environmental conditions such as water bodies and vegetation coupled with temperature increase are breeding more mosquitoes. Villages that are far from rivers and the national park and with lower populations are classified as mild and cold spots for malaria.

Fig. 9.

Participatory GIS map showing malaria hotspots in A: Malipati and B: Mahlanguleni. Red dots represents malaria hotspots, green dots, mild malaria hotspots and green dots malaria cold spots. The red lines represent rivers, blue polygons represent wetlands and redlines major roads

Fig. 10.

Participatory GIS maps for The Chitsa community showing malaria hotspots. Red dots represents malaria hotspots, green dots, mild malaria hotspots and green dots malaria cold spots. The red lines represent rivers, blue polygons represent wetlands and redlines major roads

In Chiredzi north (Mkwasine community) a community dominated my sugar cane small holder farmers portray that malaria hotspots are close to rivers, poorly managed and maintained irrigation canals and homesteads as well as compounds next to sugarcane farms which are breeding grounds for malaria vectors (Fig. 11). The participatory maps highlight that communities have a spatial appreciation of areas they classify as malaria hotspots and this indigenous and local knowledge can be factored into malaria control programmes. Not only are communities spatially aware but they also comprehend the correlation between climate change, environmental factors, and malaria incidence.

Fig. 11.

Participatory map for the Chiredzi north (Mkwasine community) showing malaria hotspots. Red dots represents malaria hotspots, green dots, mild malaria hotspots and green dots malaria cold spots. The red lines represent rivers, blue polygons represent wetlands and redlines major roads

Lessons learned and conclusions

The beginning point of the study was to determine if secondary data and citizen science or knowledge be combined to improve knowledge of the link between climatic, environmental factors and malaria incidence in Chiredzi District, Zimbabwe. Secondly, the question of how a joint vision can be developed towards malaria elimination was raised. The study presents emerging evidence that there is a strong correlation between climate change and malaria incidence, emphasizing the positive relationship between increased in average annual maximum temperature, rainfall, and malaria cases. From the study it also emerges that the change in climate has meant that the spatial spread of malaria incidence has also increased. However, the increase in malaria incidence is not only attributed to climate but other environmental and socio-economic factors such as migration, poverty, and ineffective malaria control programmes. The change in climate also exacerbates these environmental and socio- economic factors which leads to malaria incidence. It is argued that future malaria prevention programs be informed by the change in climate, socio-economic and environmental factors. Likewise, a combination of conventional scientific malaria control programmes and indigenous malaria control methods can be suggested as a pathway towards malaria control. Further studies with extended datasets that span a longer period need to be carried out to bolster the evidence linking climate change to malaria. Forecasting malaria incidence based on current climate, environmental and socio-economic conditions is crucial for advocating transformative malaria prevention programs, emphasizing the importance of inclusive partnership and adaptation to a changing climate. New malaria prevention programmes that consider the impact of a changing climate on malaria, local environmental and socio-economic factors need to be devised.

Author contributions

WM: conceptualization, methodology, investigation, data curation, writing—original draft preparation, software, validation, visualization, formal analysis, resources, writing—review and editing, supervision, project administration, funding acquisition. NBS: conceptualization, methodology, investigation, data curation, validation, visualization, formal analysis. AN: supervision, project administration, investigation, resources and writing—original draft. CZ: supervision, project administration, investigation, resources and writing—original draft. BD: investigation, resources and writing—original draft, writing—review and editing. BM: investigation, resources and writing—review and editing. All authors have read and agreed to the published version of the manuscript.

Funding

The author(s) disclosed receipt of the following financial support for the research: this work was supported by the Global Institute for Disease Elimination (GLIDE), Falcon Awards Grant number (FADE4C/06).

Data availability

The datasets [GENERATED/ANALYZED] for this study can be made available by the authors on request.

Declarations

Ethics approval and consent to participate

The study was approved by the Chiredzi Rural District Council and Ministry of Health and Childcare Zimbabwe District. The local Chiefs and local leaders where informed about our study and they gave approval for us to conduct workshops. The workshop participants gave their informed consent to participate in the workshops. Our study obtained ethical clearance form University of Johannesburg.

Competing interests

The authors declare no competing interests.