@article{fdi:010088929,
  title = {{E}nhancing understanding of the impact of climate change on malaria in {W}est {A}frica using the {V}ector-{B}orne {D}isease {C}ommunity {M}odel of the {I}nternational {C}enter for {T}heoretical {P}hysics ({VECTRI}) and the bias-corrected {P}hase 6 {C}oupled {M}odel {I}ntercomparison {P}roject {D}ata ({CMIP}6)},
  author = {{F}all, {P}. and {D}iouf, {I}. and {D}eme, {A}. and {D}iouf, {S}. and {S}ene, {D}. and {S}ultan, {B}enjamin and {J}anicot, {S}erge},
  editor = {},
  language = {{ENG}},
  abstract = {{I}n sub-{S}aharan {A}frica, temperatures are generally conducive to malaria transmission, and rainfall provides mosquitoes with optimal breeding conditions. {T}he objective of this study is to assess the impact of future climate change on malaria transmission in {W}est {A}frica using community-based vector-borne disease models, {TRI}este ({VECTRI}). {T}his {VECTRI} model, based on bias-corrected data from the {P}hase 6 {C}oupled {M}odel {I}ntercomparison {P}roject ({CMIP}6), was used to simulate malaria parameters, such as the entomological inoculation rate ({EIR}). {D}ue to the lack of data on confirmed malaria cases throughout {W}est {A}frica, we first validated the forced {VECTRI} model with {CMIP}6 data in {S}enegal. {T}his comparative study between observed malaria data from the {N}ational {M}alaria {C}ontrol {P}rogram in {S}enegal ({P}rogramme {N}ational de {L}utte contre le {P}aludisme, {PNLP}, {PNLP}) and malaria simulation data with the {VECTRI} ({EIR}) model has shown the ability of the biological model to simulate malaria transmission in {S}enegal. {W}e then used the {VECTRI} model to reproduce the historical characteristics of malaria in {W}est {A}frica and quantify the projected changes with two {S}hared {S}ocio-economic {P}athways ({SSP}s). {T}he method adopted consists of first studying the climate in {W}est {A}frica for a historical period (1950-2014), then evaluating the performance of {VECTRI} to simulate malaria over the same period (1950-2014), and finally studying the impact of projected climate change on malaria in a future period (2015-2100) according to the ssp245 ssp585 scenario. {T}he results showed that low-latitude (southern) regions with abundant rainfall are the areas most affected by malaria transmission. {T}wo transmission peaks are observed in {J}une and {O}ctober, with a period of high transmission extending from {M}ay to {N}ovember. {I}n contrast to regions with high latitudes in the north, semi-arid zones experience a relatively brief transmission period that occurs between {A}ugust, {S}eptember, and {O}ctober, with the peak observed in {S}eptember. {R}egarding projections based on the ssp585 scenario, the results indicate that, in general, malaria prevalence will gradually decrease in {W}est {A}frica in the distant future. {B}ut the period of high transmission will tend to expand in the future. {I}n addition, the shift of malaria prevalence from already affected areas to more suitable areas due to climate change is observed. {S}imilar results were also observed with the ssp245 scenario regarding the projection of malaria prevalence. {I}n contrast, the ssp245 scenario predicts an increase in malaria prevalence in the distant future, while the ssp585 scenario predicts a decrease. {T}hese findings are valuable for decision makers in developing public health initiatives in {W}est {A}frica to mitigate the impact of this disease in the region in the context of climate change.},
  keywords = {climate change ; malaria ; {VECTRI} ; {W}est {A}frica ; bias-corrected {CMIP}6 ; {AFRIQUE} {DE} {L}'{OUEST}},
  booktitle = {},
  journal = {{M}icrobiology {R}esearch},
  volume = {14},
  numero = {4},
  pages = {2148--2180},
  year = {2023},
  DOI = {10.3390/microbiolres14040145},
  URL = {https://www.documentation.ird.fr/hor/fdi:010088929},
}