From 2012 onwards, an increasing trend of malaria cases across all three demographic groups was observed. Cases among males and females older than 5 years peaked in 2016 with 98,645 and 116,627 cases, respectively (Fig. 1). Cases among children under the age of 5 years, kept increasing with an observed peak in 2018 with 84,440 cases.
Fig. 1Annual trends in numbers of malaria cases, stratified by three demographic groups in Rwanda from 2012 to 2022
For children under the age of 5 years, the median number of cases per district varied significantly, with some districts like Ngoma experiencing a median of 37,380 cases, illustrating a higher burden of malaria in these younger populations. The SD for this group indicates variability in case numbers, with districts like Kayonza and Ngoma (Eastern Province) showing a wide dispersion in the data (Table 1). The minimum and maximum for children under the age of 5 years further highlight the disparity between districts, ranging from as low as 23 in Nyabihu (Northern Province) to as high as 84,440 in Ngoma (Eastern Province) suggesting substantial heterogeneity in malaria burden among districts (Table 1).
For males above 5 years of age, the median cases also exhibited substantial variation, with districts like Nyabihu and Musanze (Northern Province) on the lower end, while others such as Kamonyi (Southern Province) and Bugesera (Eastern Province) showed higher medians (Table 1).
Similarly, for females above 5 years of age, the median cases by district revealed heterogeneity, with districts like Burera and Nyabihu on the lower spectrum, while others such as Kamonyi (Southern Province) and Bugesera (Eastern Province) had higher median numbers. The minimum and maximum in this demographic group underscore the heterogeneity in malaria burden across the country, with significant differences between districts’ lowest and highest recorded cases.
Table 1 Descriptive statistics of malaria cases distributed by age and sex demographics and districts of Rwanda between 2012 and 2022Aggregated malaria incidence rates per 1000 individuals for the period 2012–2022 are detailed across various districts, stratified by three demographic groups as shown in Table 2. The district of Ngoma recorded the highest incidence rate among children under the age of 5 years, with 670.5 cases per 1000 children. Conversely, the district of Nyabihu reported the lowest rate in this group, with 2.6 cases per 1000 children. Among males above 5 years of age, the highest incidence rate was observed in Ngoma with 273.7 cases per 1000, while Musanze had the lowest with 12.6 cases per 1000. Similarly, females above 5 years of age in Ngoma experienced the highest incidence rate of 313.9 cases per 1000 individuals, whereas Burera reported the lowest rate at 6.0 cases per 1000.
Table 2 Malaria incidence rates per 1000 individuals in Rwanda from 2012–2022 by district and demographic groupThe spatio scan statistics highlighting the high-risk malaria clusters in Rwanda, stratified by demographic groups between 2012 and 2022 are depicted in Fig. 2. For children under the age of 5, the clusters identified during 2015–2019 include districts such as Bugesera, Gasabo, Gisagara among others, with an observed to expected case ratio of 2.29, indicating that the observed cases were over twice the expected number. This cluster also shows a significant log likelihood ratio of 584,362, strongly suggesting a higher-than-expected malaria incidence, with a P-value of less than 0.001, confirming the statistical significance of these findings. Similarly, for males above 5 years, the period 2014–2018 shows a cluster encompassing additional districts like Karongi and Nyamagabe, with an observed to expected ratio of 2.3 and a log likelihood ratio of 1,146,688, also significant at a P-value of less than 0.001. This indicates a similarly high risk compared to national averages, with significantly more cases observed than expected. The clusters for females above 5 years of age during the same period exhibit an observed to expected ratio of 2.39 and a log likelihood ratio of 1,469,933, with the clustering extending into districts such as Kirehe and Rulindo. The P-value of less than 0.001 for these clusters again supports the presence of a significantly higher incidence of malaria than expected based on the national average. These statistics substantiate the clusters shown in all maps, with districts marked in red indicating a number of observed malaria cases surpassing expected values.
Fig. 2Spatial distribution of high malaria risk clusters in Rwanda from 2012–2022, stratified by demographic groups and their corresponding cluster identification periods. The left map indicates clusters for children under the aged of 5 years during 2015–2019, the middle map denotes clusters for males above 5 years of age during 2014–2018, and the right map illustrates clusters for females above 5 years of age during 2014–2018. Districts coloured in red represent areas where the number of observed malaria cases was higher than expected, signalling a higher risk of reported malaria cases compared to the national average
A comprehensive summary of the spatio scan analysis from 2012 to 2022, depicted in Table 3 reveals malaria clusters across various demographic groups. The analysis indicates that for children under the age of 5 years, between 2015 and 2019, a total of 1,637,971 malaria cases were observed in districts including Bugesera, Gasabo, Gisagara among others. These cases notably surpassed the expected count of 713,780, based on the underlying population of 650,000. The expected number of cases is defined as the number of cases that would be expected based on the underlying population at risk in the absence of any spatial or temporal clustering. The high significance of this cluster is further emphasized by a log likelihood ratio of 584,362 and a P-value of less than 0.001. Similarly, for males aged above 5 years from 2014 to 2018, the observed cases totaled 3,032,237 across several districts, significantly exceeding the expected 1,318,150 cases derived from a population of 2,324,912. This discrepancy is highlighted by a log likelihood ratio of 1,146,688 and a P-value of less than 0.001. Additionally, the cluster for females aged above 5 years during the same timeframe involved 3,611,089 observed malaria cases, far exceeding the expected 1,510,183 cases from a population of 2,435,551. This clustering is confirmed as significant by a log likelihood ratio of 1,469,933 and a P-value of less than 0.001 (Table 3).
Table 3 Malaria cluster analysis summary for Rwanda in 2012–2022, stratified by demographic groupThroughout the 2012 to 2022 timeframe, the spatio-temporal analysis of malaria risk among children under the age of 5 years has revealed distinct patterns of elevated RR in certain districts (Fig. 3). Initially, the district of Ngoma was notable with the highest RR in 2014, reaching 3.24 (95% CI: 3.22–3.26). Over the subsequent years, districts such as Gisagara, Huye, Kayonza, and Ruhango were consistently highlighted for their high RRs. Notably, Gisagara district exhibited a significant increase in RR, with a peak at 2.13 (95% CI: 2.12–2.15) in 2013 and surging at 2.64 (95% CI: 2.63–2.65) in 2015. Similarly, Huye district showed an increase in RR to 3.39 (95% CI: 3.38–3.41) in 2015. Ngoma district displayed the most substantial RR during this period, with a peak of 7.00 (95% CI: 6.98–7.03) in 2016 (Fig. 3).
Fig. 3Map of Rwanda with spatio-temporal relative risks (RRs) of malaria for children under the age of 5 years from 2012 to 2022
Over the decade-long study from 2012 to 2022, a discernible pattern of malaria risk among males aged above 5 years was observed, with significant variances across different districts. The investigation began with Kirehe district exhibiting a notable RR of 1.86 (95% CI: 1.84–1.87) in 2012 (Fig. 4). In subsequent years, several districts emerged as recurrent hotspots with elevated RR values. Ngoma district, for instance, showed elevated RRs throughout the study period, with a peak RR of 5.70 (95% CI: 5.68–5.72) in 2016. Similarly, Kayonza district displayed consistently high RRs, notably reaching 4.59 (95% CI: 4.57–4.60) in 2016. Ruhango district also demonstrated persistently high RRs, especially in 2017 with a RR of 4.67 (95% CI: 4.65–4.69). Despite a general trend of declining RRs by 2020, the districts of Ngoma, Kayonza, and Ruhango continued to report elevated risks.
Fig. 4Map of Rwanda with spatio-temporal relative risks (RRs) of malaria for males aged above 5 years from 2012 to 2022
In the comprehensive analysis conducted from 2012 to 2022, notable trends in malaria risk among females aged above 5 years were observed, highlighting significant geographic heterogeneity in risk levels across different districts (Fig. 5). The investigation began with districts of Kirehe and Nyagatare which demonstrated elevated RRs of 1.77 (95% CI: 1.76–1.79) and 1.76 (95% CI: 1.75–1.78), respectively, in 2012. However, it was from 2014 onwards that certain districts consistently emerged with particularly high RRs (Fig. 5). In 2014, Kirehe district reported a markedly high RR of 3.45 (95% CI: 3.43–3.46), and Huye district also showed a substantial increase to 3.32 (95% CI: 3.30–3.33). The year 2015 saw Ngoma district reaching the decade peak with a RR of 5.04 (95% CI: 5.02–5.05), with Huye and Kayonza districts following closely, peaking at 4.35 (95% CI: 4.34–4.36) and 3.92 (95% CI: 3.91–3.94), respectively. Ruhango emerged as a district with an elevated malaria risk, peaking at a RR of 4.62 in 2017. Kayonza, Nyanza, and Nyamasheke were also identified as high-risk districts, consistently reporting RRs above 2.5 from 2014 to 2018 (Fig. 5). Toward the end of the study period, there was a general decline in RRs. However, Ruhango and Gisagara districts continued to manifest elevated risks of around 1.10 in 2020.
Fig. 5Map of Rwanda with spatio-temporal relative risks (RRs) of malaria for females aged above 5 years from 2012 to 2022
The time plots delineate the malaria transmission risk across various districts in Rwanda, stratified by demographic groups and annotated for clarity (Fig. 6). Plot A illustrates the trend for children under the age of 5 years, where districts such as Ngoma, Huye, Kayonza, and Ruhango exhibit an ascending and descending trajectory in RR from 2012 to 2022. In contrast, Gisagara and Bugesera districts demonstrate a relatively stable RR (Fig. 6).
Plot B, representing males above 5 years of age, highlights that Ngoma, Ruhango, Kayonza, and Huye districts faced a consistent increase in RR. The peak of the risk was observed in Ngoma district in 2016 (Fig. 6).
In Plot C, focusing on females above 5 years of age, districts such as Ngoma, Kayonza, Nyanza, and Huye are depicted with RRs of 2 and above (Fig. 6). In these plots, colors indicate RR values above 1 for some years in the study period, signifying a higher risk of malaria transmission. In contrast, those areas without color or unhighlighted represent districts with a RR of 1 or below.
Fig. 6Combined time plots illustrating the relative risk (RR) of malaria infection for three demographic groups in districts with RR greater than 1 in Rwanda from 2012 to 2022. A Children under the age of 5 years; B males above 5 years of age; and C females above 5 years of age. Each colored line corresponds to a district that reported a RR greater than the national average during the study period. The color key denotes the specific districts
Interactive web applicationAn interactive web application has been created using Shiny (https://paulamoraga.shinyapps.io/malariarwandaapp/), The dashboard offers tools such as interactive maps, a database, heat maps, and risk analysis, enabling users to explore malaria data across Rwanda for various demographic groups from 2012 to 2022. It visualizes data like population, cases, and RR, providing insights into spatial and temporal trends to support public health planning and interventions [30].
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