@article{fdi:010085988,
  title = {{S}ub-national tailoring of seasonal malaria chemoprevention in {M}ali based on malaria surveillance and rainfall data},
  author = {{C}issoko, {M}. and {S}agara, {I}. and {L}andier, {J}ordi and {G}uindo, {A}. and {S}anogo, {V}. and {C}oulibaly, {O}. {Y}. and {D}embele, {P}. and {D}ieng, {S}. and {B}ationo, {C}. {S}. and {D}iarra, {I}. and {M}agassa, {M}. {H}. and {B}erthe, {I}. and {K}atile, {A}. and {T}raore, {D}. and {D}essay, {N}adine and {G}audart, {J}.},
  editor = {},
  language = {{ENG}},
  abstract = {{B}ackground: {I}n malaria endemic countries, seasonal malaria chemoprevention ({SMC}) interventions are performed during the high malaria transmission in accordance with epidemiological surveillance data. {I}n this study we propose a predictive approach for tailoring the timing and number of cycles of {SMC} in all health districts of {M}ali based on sub-national epidemiological surveillance and rainfall data. {O}ur primary objective was to select the best of two approaches for predicting the onset of the high transmission season at the operational scale. {O}ur secondary objective was to evaluate the number of malaria cases, hospitalisations and deaths in children under 5 years of age that would be prevented annually and the additional cost that would be incurred using the best approach. {M}ethods: {F}or each of the 75 health districts of {M}ali over the study period (2014-2019), we determined (1) the onset of the rainy season period based on weekly rainfall data; (ii) the onset and duration of the high transmission season using change point analysis of weekly incidence data; and (iii) the lag between the onset of the rainy season and the onset of the high transmission. {T}wo approaches for predicting the onset of the high transmission season in 2019 were evaluated. {R}esults: {I}n the study period (2014-2019), the onset of the rainy season ranged from week ({W}) 17 ({W}17; {A}pril) to {W}34 ({A}ugust). {T}he onset of the high transmission season ranged from {W}25 ({J}une) to {W}40 ({S}eptember). {T}he lag between these two events ranged from 5 to 12 weeks. {T}he duration of the high transmission season ranged from 3 to 6 months. {T}he best of the two approaches predicted the onset of the high transmission season in 2019 to be in {J}une in two districts, in {J}uly in 46 districts, in {A}ugust in 21 districts and in {S}eptember in six districts. {U}sing our proposed approach would prevent 43,819 cases, 1943 hospitalisations and 70 deaths in children under 5 years of age annually for a minimal additional cost. {O}ur analysis shows that the number of cycles of {SMC} should be changed in 36 health districts. {C}onclusion: {A}dapting the timing of {SMC} interventions using our proposed approach could improve the prevention of malaria cases and decrease hospitalisations and deaths. {F}uture studies should be conducted to validate this approach.},
  keywords = {{M}alaria ; {H}igh transmission season ; {R}ainfall ; {S}ub-national ; {T}ailoring ; {MALI}},
  booktitle = {},
  journal = {{P}arasites and {V}ectors},
  volume = {15},
  numero = {1},
  pages = {278 [13 ]},
  ISSN = {1756-3305},
  year = {2022},
  DOI = {10.1186/s13071-022-05379-4},
  URL = {https://www.documentation.ird.fr/hor/fdi:010085988},
}