Subnational malaria burden in Sindh, Pakistan: over a decade of evidence for tailored strategies

Abstract

Background: Accurate estimates of malaria burden are crucial for allocating resources and designing effective control strategies. However, global reports often underestimate the burden in low- and middle-income countries, especially beyond the African region. This study addresses this gap by providing a longitudinal time-series analysis of malaria burden and spatio-temporal distribution in Sindh province, Pakistan.

Methods: Monthly suspected malaria cases reported from 1088 primary healthcare facilities managed by the PPHI-Sindh across 23 districts of Sindh Province (excluding seven districts of Karachi), Pakistan, were analysed over a 13-year period (2012-2024). Malaria incidence was determined by dividing total malaria cases by each health facility's catchment area population. Population-weighted estimates of malaria cases were calculated to account for variations in population size across districts. Yearly time-trend (with 95% CI), seasonal variation by month (with 95% CI), and a treemap illustrating the distribution of malaria burden across districts in Sindh.

Results: An incidence of 92 per 1000 people per annum of suspected malaria cases was reported at primary public healthcare facilities. Pooled estimates of 16.7 million cases occurred during a 13-year period, about 1.28 million cases annually. Marked heterogeneity observed in malaria burden across districts. Malaria positivity rate was 12.3%. Six districts (Khairpur, Sanghar, Naushero Feroze, Badin, Mirpurkhas, and Larkana) carried over 53% burden of malaria in Sindh. A distinct seasonal pattern with peak coinciding with the wet season and post-monsoon period was observed. Since the 2022 floods in Sindh, the malaria incidence has doubled, and it is persisting in the province.

Conclusions: The study highlights the substantial malaria burden with wet seasons and post-monsoon peaks in Sindh and identified few high-burden districts. The impact of 2022 flood seems to have persisted to 2024 and onwards, which needs immediate attention. Identification of high-burden districts could help tailor malaria control strategies. Also, the underestimation by global reports emphasizes the need for country-level and subnational analyses for informed decision-making. By addressing these gaps and refining burden estimates, Pakistan can develop more targeted strategies towards malaria control.

Keywords: GIS; High-burden; Incidence; Malaria; Seasonality; Spatio-temporal distribution; Time-series.

Fig. 1

Inclusion criteria for people’s primary healthcare initiative’s (PPHI) facilities in the province of Sindh, Pakistan

Fig. 2

Distribution of primary healthcare facilities of public sector (PPHI) in Sindh, Pakistan

Fig. 3

Yearly population-weighted average suspected malaria cases and 95% CI across 23 districts in Sindh province (2012-2024)

Fig. 4

Monthly population-weighted suspected malaria cases and 95% CI across 23 districts in Sindh province (2012–2024)

Fig. 5

Total burden of malaria (with 95% CI) during 2012–2024 according to districts in the province of Sindh, Pakistan

Fig. 6

District-wise burden of suspected malaria cases (incidence/1000) in Sindh, Pakistan (2012–2022)

Fig. 7

Population-adjusted malaria suspected burden density map by district in Sindh, Pakistan (2012–2024)