Understanding the relationship between land use and land cover and malaria in Nepal

Malaria transmission in Nepal under climate change: anticipated shifts in extent and season, and comparison with risk definitions for intervention

BACKGROUND

Climate and climate change affect the spatial pattern and seasonality of malaria risk. Season lengths and spatial extents of mapped current and future malaria transmission suitability predictions for Nepal were assessed for a combination of malaria vector and parasites: Anopheles stephensi and Plasmodium falciparum (ASPF) and An. stephensi and Plasmodium vivax (ASPV) and compared with observed estimates of malaria risk in Nepal.

METHODS

Thermal bounds of malaria transmission suitability for baseline (1960-1990) and future climate projections (RCP 4.5 and RCP 8.5 in 2030 and 2050) were extracted from global climate models and mapped for Nepal. Season length and spatial extent of suitability between baseline and future climate scenarios for ASPF and ASPV were compared using the Warren's I metric. Official 2010 DoHS risk districts (DRDs) and 2021 DoHS risk wards (DRWs), and spatiotemporal incidence trend clusters (ITCs) were overlaid on suitability season length and extent maps to assess agreement, and potential mismatches.

RESULTS

Shifts in season length and extent of malaria transmission suitability in Nepal are anticipated under both RCP 4.5 and RCP 8.5 scenarios in 2030 and 2050, compared to baseline climate. The changes are broadly consistent across both future climate scenarios for ASPF and ASPV. There will be emergence of suitability and increasing length of season for both ASPF and ASPV and decreasing length of season for ASPV by 2050. The emergence of suitability will occur in low and no-risk DRDs and outside of high and moderate-risk DRWs, season length increase will occur across all DRD categories, and outside of high and moderate-risk DRWs. The high and moderate risk DRWs of 2021 fall into ITCs with decreasing trend.

CONCLUSIONS

The study identified areas of Nepal where malaria transmission suitability will emerge, disappear, increase, and decrease in the future. However, most of these areas are anticipated outside of the government's current and previously designated high and moderate-risk areas, and thus outside the focus of vector control interventions. Public health officials could use these anticipated changing areas of malaria risk to inform vector control interventions for eliminating malaria from the country, and to prevent malaria resurgence.

Spatio-Temporal Variability of Malaria Incidence in the Health District of Kati, Mali, 2015-2019

INTRODUCTION

Despite the implementation of control strategies at the national scale, the malaria burden remains high in Mali, with more than 2.8 million cases reported in 2019. In this context, a new approach is needed, which accounts for the spatio-temporal variability of malaria transmission at the local scale. This study aimed to describe the spatio-temporal variability of malaria incidence and the associated meteorological and environmental factors in the health district of Kati, Mali.

METHODS

Daily malaria cases were collected from the consultation records of the 35 health areas of Kati's health district, for the period 2015-2019. Data on rainfall, relative humidity, temperature, wind speed, the normalized difference vegetation index, air pressure, and land use-land cover were extracted from open-access remote sensing sources, while data on the Niger River's height and flow were obtained from the National Department of Hydraulics. To reduce the dimension and account for collinearity, strongly correlated meteorological and environmental variables were combined into synthetic indicators (SI), using a principal component analysis. A generalized additive model was built to determine the lag and the relationship between the main SIs and malaria incidence. The transmission periods were determined using a change-point analysis. High-risk clusters (hotspots) were detected using the SatScan method and were ranked according to risk level, using a classification and regression tree analysis.

RESULTS

The peak of the malaria incidence generally occurred in October. Peak incidence decreased from 60 cases per 1000 person-weeks in 2015, to 27 cases per 1000 person-weeks in 2019. The relationship between the first SI (river flow and height, relative humidity, and rainfall) and malaria incidence was positive and almost linear. A non-linear relationship was found between the second SI (air pressure and temperature) and malaria incidence. Two transmission periods were determined per year: a low transmission period from January to July-corresponding to a persisting transmission during the dry season-and a high transmission period from July to December. The spatial distribution of malaria hotspots varied according to the transmission period.

DISCUSSION

Our study confirmed the important variability of malaria incidence and found malaria transmission to be associated with several meteorological and environmental factors in the Kati district. The persistence of malaria during the dry season and the spatio-temporal variability of malaria hotspots reinforce the need for innovative and targeted strategies.

Social determinants of health and the double burden of disease in Nepal: a secondary analysis

Background

As the global burden of disease evolves, lower-resource countries like Nepal face a double burden of non-communicable and infectious disease. Rapid adaptation is required for Nepal’s health system to provide life-long, person-centred care while simultaneously improving quality of infectious disease services. Social determinants of health be key in addressing health disparities and could direct policy decisions to promote health and manage the disease burden. Thus, we explore the association of social determinants with the double burden of disease in Nepal.

Methods

This is a retrospective, ecological, cross-sectional analysis of infectious and non-communicable disease outcome data (2017 to 2019) and data on social determinants of health (2011 to 2013) for 753 municipalities in Nepal. Multinomial logistic regression was conducted to evaluate the associations between social determinants and disease burden.

Results

The ‘high-burden’ combined double burden (non-communicable and infectious disease) outcome was associated with more accessible municipalities, (adjOR3.94[95%CI2.94–5.28]), municipalities with higher proportions of vaccine coverage (adjOR12.49[95%CI3.05–51.09]) and malnutrition (adjOR9.19E103[95%CI19.68E42-8.72E164]), lower average number of people per household (adjOR0.32[95%CI0.22–0.47]) and lower indigenous population (adjOR0.20[95%CI0.06–0.65]) compared to the ‘low-burden’ category on multivariable analysis. ‘High-burden’ of non-communicable disease was associated with more accessible municipalities (adjOR1.93[95%CI1.45–2.57]), higher female proportion within the municipality (adjOR1.69E8[95%CI3227.74–8.82E12]), nutritional deficiency (adjOR1.39E17[95%CI11799.83–1.64E30]) and malnutrition (adjOR2.17E131[95%CI4.41E79-1.07E183]) and lower proportions of population under five years (adjOR1.05E-10[95%CI9.95E-18–0.001]), indigenous population (adjOR0.32[95%CI0.11–0.91]), average people per household (adjOR0.44[95%CI0.26–0.73]) and households with no piped water (adjOR0.21[95%CI0.09–0.49]), compared to the ‘low-burden’ category on adjusted analysis. ‘High burden’ of infectious disease was also associated with more accessible municipalities (adjOR4.29[95%CI3.05–6.05]), higher proportions of population under five years (adjOR3.78E9[95%CI9418.25–1.51E15]), vaccine coverage (adjOR25.42[95%CI7.85–82.29]) and malnutrition (adjOR4.29E41[95%CI12408.29–1.48E79]) and lower proportions of households using firewood as fuel (adjOR0.39[95%CI0.20–0.79]) (‘moderate-burden’ category only) compared to ‘low-burden’.

Conclusions

While this study produced imprecise estimates and cannot be interpreted for individual risk, more accessible municipalities were consistently associated with higher disease burden than remote areas. Female sex, lower average number per household, non-indigenous population and poor nutrition were also associated with higher burden of disease and offer targets to direct interventions to reduce the burden of infectious and non-communicable disease and manage the double burden of disease in Nepal.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12889-022-13905-3.