Climate change, malaria and neglected tropical diseases: a scoping review

Abstract

To explore the effects of climate change on malaria and 20 neglected tropical diseases (NTDs), and potential effect amelioration through mitigation and adaptation, we searched for papers published from January 2010 to October 2023. We descriptively synthesised extracted data. We analysed numbers of papers meeting our inclusion criteria by country and national disease burden, healthcare access and quality index (HAQI), as well as by climate vulnerability score. From 42 693 retrieved records, 1543 full-text papers were assessed. Of 511 papers meeting the inclusion criteria, 185 studied malaria, 181 dengue and chikungunya and 53 leishmaniasis; other NTDs were relatively understudied. Mitigation was considered in 174 papers (34%) and adaption strategies in 24 (5%). Amplitude and direction of effects of climate change on malaria and NTDs are likely to vary by disease and location, be non-linear and evolve over time. Available analyses do not allow confident prediction of the overall global impact of climate change on these diseases. For dengue and chikungunya and the group of non-vector-borne NTDs, the literature privileged consideration of current low-burden countries with a high HAQI. No leishmaniasis papers considered outcomes in East Africa. Comprehensive, collaborative and standardised modelling efforts are needed to better understand how climate change will directly and indirectly affect malaria and NTDs.

Figure 1.

Comparison of Intergovernmental Panel on Climate Change (IPCC) scenarios used in papers that met this review's inclusion criteria. The different categories of scenario (special report on emission scenarios [SRES; released in 2000]; representative concentration pathways [RCPs; 2014]; shared socioeconomic pathways [SSP; 2021]; scenarios from the IPCC Sixth Assessment Report Working Group III [AR6 WGIII; 2022]) are laid out in columns against the equivalent scenarios within the full RCP scheme, which are laid out in rows; some of the RCP scenarios (RCP1.9, RCP3.4 and RCP7) were added after the original 2014 publication of the RCP system. (The RCPs were the most commonly applied scenarios used in papers that met this review's inclusion criteria.) Further explanations of all of these scenario categories are included in Box 1.

Figure 2.

Records included and excluded at each review stage.

Figure 3.

Number of papers by year and total number of papers meeting the inclusion criteria for each (A) disease or disease group, and (B) type of study.

Figure 4.

Geographical coverage of papers by disease. Colours represent the total number of papers that met the inclusion criteria, per disease, across countries.

Figure 5.

Numbers of papers meeting the inclusion criteria by disease or disease group, compared with country-level (A) DALYs for the disease or disease group; (B) health access and quality index; and (C) climate vulnerability score. Studies with outcomes reported at global level (for all countries) were removed for these analyses. Each circle represents one country; superimposition of multiple circles makes some look darker than others. Lines show locally estimated scatterplot smoothing (LOESS)-generated local polynomial regression.