The study conducted in Luapula and southern provinces of Zambia over a ten-year period from 2010 to 2020 sheds light on the intricate relationships among climate change, environmental factors, and malaria incidence. In Luapula Province, a positive correlation was observed between malaria incidence rates and maximum and minimum temperatures. This positive association reflects the broader trend of climate change, with rising temperatures potentially facilitating the spread of malaria (Ashton et al., 2017). Furthermore, the negative correlation between malaria incidence and daily precipitation indicates that reduced rainfall is linked to increased malaria incidence. This aligns with the adverse effects of climate change, which include decreased precipitation and its impact on malaria transmission (World Health Organization, 2008). This study also highlights the influence of climate change on rainfall patterns, which has led to fluctuations over the years in Luapula Province. These fluctuations may be attributed to changing climate conditions, which affect malaria dynamics.
(i) The effects of climate change on the malaria incidence rate in relation to rainfall and temperature variation patterns in Zambia over a ten-year period beginning in 2010
Luapula Province
The results of the Pearson correlation test revealed a strong positive (0.043) correlation between the malaria incidence rate and maximum temperature. There was also a positive correlation (0.152) between the malaria incidence rate and minimum temperature. Similarly, there was a negative correlation (-0.623) between the malaria incidence rate and daily precipitation (mm) corrected between 2010 and 2020. Furthermore, analysis also indicated that there was a strong association between the malaria incidence rate and daily precipitation corrected between 2010 and 2020, with a p value of 0.041, which was statistically significant at 0.05. The data analysis also revealed a negative (-0.608) correlation between the malaria incidence rate and annual rainfall. The Pearson correlation coefficient also revealed a strong association between the malaria incidence rate and annual rainfall, with a p value of 0.047 indicating statistical significance at 0.05.
Studies, such as those conducted by Ashton et al. (2017) and the World Health Organization (2008), have also highlighted the positive relationship between temperature and malaria incidence. Increasing temperatures can extend the geographical range of malaria vectors and accelerate the spread of the malaria parasite within mosquitoes, potentially leading to increased malaria transmission. The inverse relationship between malaria incidence and daily precipitation has been documented in previous studies, emphasizing the role of water availability in creating suitable breeding habitats for mosquito vectors. Reduced precipitation can lead to the creation of stagnant water bodies that are ideal for mosquito larvae to thrive, as mentioned by the World Health Organization (2008). The strong association between malaria incidence and annual rainfall, as indicated by the significant p value, underlines the importance of understanding long-term precipitation patterns in malaria-endemic regions. Such patterns can provide insights into the likelihood of malaria outbreaks, especially in areas where rainfall is a key driver of mosquito breeding, as supported by research on climate and malaria transmission dynamics (Ashton et al., 2017; World Health Organization, 2008). As a result, this study further revealed a high fluctuating trend in rainfall that was recorded from 2010 to 2020, with a 1058.0 mm mean annual rainfall, and the maximum total rainfall was observed in 2017 (1434.4 mm), while the minimum rainfall was observed in 2016 (801.6 mm). The results obtained showed an association between monthly malaria cases and the climatic/meteorological variables temperature and rainfall.
Southern Province
The Pearson correlation coefficient was calculated to determine the relationship between malaria incidence rates and meteorological/climatic factors. The results revealed that there was a negative correlation between the relative maximum temperature (-0.263) and minimum temperature (-0.276). On the other hand, there was a positive correlation (0.084) between the mean temperature and malaria incidence rate. There was also a strong positive correlation between malaria incidence rates and rainfall. The results from the Pearson correlation test between malaria incidence rates and daily precipitation corrected (mm/day) from 2010 to 2020 revealed that there was a positive correlation between malaria incidence rates and daily precipitation corrected (mm/day). Additionally, there was no statistically significant association between the Malaria incidence rate and minimum rainfall (mm/day), with a p value of 0.719 indicating a significant difference of 0.05.
This negative relationship indicates that as temperatures increase, the incidence of malaria tends to decrease. These findings are consistent with those of several previous studies, which have shown that extreme heat can negatively impact mosquito survival and reduce malaria transmission (Shimaponda-Mataa et al.,2017). These findings contribute to the growing body of research investigating the links between meteorological and climatic factors and malaria incidence. These results reinforce the importance of considering these factors in malaria control strategies and adapting interventions to the specific weather conditions of different regions. Understanding the complex relationships between temperature and rainfall variables and malaria transmission is critical in developing effective and targeted measures for combating this disease, particularly in the face of climate change. The significance of these findings lies in their potential to inform evidence-based strategies for malaria prevention and control.
(II) The role of climate change in the observed increase or decrease in Malaria in Zambia over a ten-year period from 2010 to 2020
The data analysis in this study revealed that there was a higher incidence of floods recorded in Luapula Province and a high incidence of droughts in the southern province of Zambia as of 2020. The results of the averaged VHI for Luapula Province showed that there was a positive correlation between land and vegetation. Furthermore, the data showed that there was a fluctuating trend in vegetation availability over the ten-year period. However, Luapula Province is more prone to harboring larvae for mosquitoes with favorable or suitable environmental conditions for survival, whereas in the southern province, the high number of droughts recorded has impacted the vegetation health index, leading to harsh environmental conditions for the survival and harboring of mosquito larvae.
According to the data generated, the Vegetable Health Index for the yearly percentage of drought area for the province showed that in 2019, the southern province had the highest (64%) percentage of drought recorded during a ten-year period. In Luapula Province, the highest percentage recorded was 31% of the yearly percentage of drought area for the province, and drought was recorded in 2012.
Similarly, Nygren et al. (2014) collected weekly malaria data from 2011 to 2013 and used the normalized difference vegetation index (NDVI), night surface temperature, rainfall, and night dew point to model health facility-level malaria transmission within the southern province. Their results revealed a significant association with environmental variables (dewing point, temperature, and NDVI) across low, moderate, and high transmission zones (Nygren et al., 2014). This study is important because of its contribution to the growing body of knowledge linking climate change, environmental conditions, and malaria transmission. By elucidating the distinct climate-related challenges faced by different regions within Zambia, this research provides critical insights for malaria control and adaptation strategies. Recognizing the impact of floods, droughts, and vegetation health on mosquito breeding and malaria transmission is vital for tailoring interventions to specific local conditions and effectively combating this disease in the context of a changing climate.
5.3 Role of environmental land use combined with climate change in the observed increase or decrease in Malaria incidence over a ten-year period from 2010 to 2020 in Zambia
The study revealed that in 2010, the southern province had 216 kha of tree cover, extending over 2.5% of its land area. In 2021, 1.96 kha of tree cover was lost, equivalent to 564 kt of CO₂ emissions. In 2010, Luapula had 2.13 Mha of tree cover, extending over 43% of its land area. In 2021, 20.6 kha of tree cover was lost, equivalent to 7.81 Mt of CO₂ emissions.
Furthermore, data obtained from ZamStats (2022) reveal that in Luapula Province, 194,520 people live in urban areas, while the majority of the population (797,407) lives in rural areas. In the southern province, 392,175 people live in urban areas, and 1,197,751 people (majority) live in rural areas.
As of 2020, many settlements in Luapula Province have an estimated population density of 20 per km²; the total area of the province is 50,567 km² and characterized by its rural nature. In 2010, the total area of the southern province was 85,283 km², and the population density was 18.60 per km² (Grid3, 2022). These data imply that Luapula Province has a large surface area and vegetation that provide suitable conditions for mosquito larvae to survive, and the majority of the population lives in rural areas of the province and has more exposure to mosquito bites, as these areas have good VHIs that are between 40 and 60 over a ten-year period.
However, in the southern province, there is a poor vegetation health index with high records of droughts due to urban settlements and high cases of deforestation, which have led to poor environmental conditions that have affected the survival of mosquito larvae in these areas.
Furthermore, an example of a district-wide study was conducted in the Nchelenge district in Luapula Province using household-level cross-sectional surveys conducted every two months between 2012 and 2015 (Pinchoff et al., 2015, 2016).