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Table 2 Parameters and input data used by LiST and Spectrum-Malaria in projections for DRC and Zambia

From: Impact of malaria interventions on child mortality in endemic African settings: comparison and alignment between LiST and Spectrum-Malaria model

Parameter (2015, unless otherwise indicated) DRC Zambia Data sources & definitions
Spectrum-Malaria LiST Spectrum-Malaria LiST Spectrum-Malaria LiST
Population at malaria riska 97.1% 91% 100% 98% All-age population living where PfPR among 2–9 years >0 [2, 19] Women exposed to P. falciparum malaria [50]
Population 0–4 years (including children living not at malaria risk) 12,373,927 13,682,392 2,848,069 2,888,817 United Nations Population Division [51]
Index for seasonality in malaria transmission 0.36 NA 1.64 NA Coefficient of variation in EIR over a year, defined as the standard deviation divided by the year-average of monthly EIR [34]; country estimates from Malaria Atlas Project [2, 19]
Prevalence of P. falciparum infection in children 2–9 years, average over 2000–2002 64% NA 35% NA Malaria Atlas Project [19]  
Malaria deaths in children 0–59 months (% of all-cause deaths) 33,038 47,473 (16%) 2734 2723 (5.9%) WHO (http://www.who.int/healthinfo/global_burden_disease/estimates/en/index3.html and [1]) WHO
All-cause under-5 deaths NA 298,200 NA 45,916 NA UN Inter-Agency Group for Child Mortality Estimation [20]
Malaria deaths in 5–14 years 3258 NA 2226 NA WHO [1]; share of 5–14 versus 15+ years as for malaria cases [2, 19] NA
Malaria deaths in 15+ years 2936 NA 2074 NA  
Malaria cases i.e. disease episodes in 0–4 years 8,231,156 NA 1,188,935 NA WHO [1]; the share of 0–4 years in WHO’s all age estimate taken from Malaria Atlas Project [2, 19] NA
  1. Abbreviations: EIR Entomological Inoculation Rate, LiST Lives Saved Tool, DRC Democratic Republic of the Congo, MAP Malaria Atlas Project, P. falciparum Plasmodium falciparum, NA not available
  2. aThe population at risk of malaria does not influence impact calculations, but it is used in the OneHealth Tool costing as the ‘Population in Need’ (PIN) that would need to get various services like ITNs, IRS spraying, etc. (Equation for number of services: Target Population * PIN * Coverage)