Estimating the potential public health impact of seasonal malaria chemoprevention in African children

Abstract

Seasonal malaria chemoprevention, previously known as intermittent preventive treatment in children, is highly effective in areas with a short malaria transmission season. Here we assess seasonality in malaria incidence data and define a predictor of seasonality based on rainfall. We then use spatial rainfall, malaria endemicity and population data to identify areas likely to have highly seasonal malaria incidence, and estimate the population at risk and malaria burden in areas where seasonal malaria chemoprevention would be appropriate. We estimate that in areas suitable for seasonal malaria chemoprevention, there are 39 million children under 5 years of age, who experience 33.7 million malaria episodes and 152,000 childhood deaths from malaria each year. The majority of this burden occurs in the Sahelian or sub-Sahelian regions of Africa. Our data suggest that seasonal malaria chemoprevention has the potential to avert several million malaria cases and tens of thousands of childhood deaths each year if successfully delivered to the populations at risk.

Figures

Figure 1. Analysis of rainfall as a predictor of epidemiology suitable for SMC.

(a) Receiver operating characteristic curve for binary indicator variables describing the percentage of the annual total rainfall occurring in 3 consecutive months. Dummy variables were created for 5% intervals between 0% and 100%. Observed values of cumulative rainfall in 3 months ranged from 33.8%–84.5%. The best indicator of SMC areas was rainfall greater than 60% in 3 months (sensitivity 95.0%, specificity of 73.5%). The black line indicates the reference line of no discrimination. (b) Maximum percentage of annual rainfall within 3 consecutive months compared with maximum percentage of malaria incidence within four consecutive months. The horizontal red line shows the cumulative incidence threshold within 4 months specified by definition B. The vertical red line shows discrimination of the data points by the best indicator based on rainfall (60% within 3 months).

Figure 2. Areas suitable for SMC implementation based on seasonality in rainfall and on malaria endemicity.

(a). The maximum proportion of annual rainfall occurring within three consecutive months. Orange-red areas are those identified as suitable for SMC based on >60% of annual rainfall in 3 months. Green–blue areas indicate areas with less than 60% of annual rainfall within 3 months. First administrative level areas are superimposed on the map. (b) The maximum proportion of annual rainfall restricted to areas with stable endemic P. falciparum, as estimated by MAP. (c) and (d) indicate rainfall seasonality in areas with prevalence above 8.8 and 17.3%, as estimated by MAP, corresponding to incidence above 0.1 and 0.2 cases per child per year, respectively.

Figure 3. Malaria cases and deaths potentially averted by SMC.

Malaria cases and malaria deaths potentially averted in all areas suitable for SMC (a,c), and in areas with incidence >0.2 cases per child per year (b,d), with varying assumptions about efficacy, monthly coverage and the fraction of the burden occurring during the SMC period. 75% was considered the best estimate of the fraction of the total annual malaria burden occurring during the SMC period in SMC areas; 60 and 90% are also shown. Solid lines show impact for 3 SMC courses, assumed to have 65% efficacy as detailed in the text. Dotted lines show impact for 4 SMC courses, assumed to have 80% efficacy. The malaria burden estimate used for these calculations was that using the WMR method: 33,677,976 malaria cases in all SMC areas with stable endemic P. falciparum, and 25,712,319 derived from the population mapped by rainfall in areas with estimate of malaria incidence >0.2/child/year. Deaths refer to the constant-case fatality rate of 4.5 per 1,000, applied to the incidence estimates.

Figure 4. Prevalence and incidence of malaria detected in SMC studies and the MAP prevalence-incidence relationship.

Data points show observed incidence against end of season prevalence from control or placebo groups in IPTc studies from Niakhar, Senegal; Hohoe, Ghana; Kambila, Mali; Bobo-Dioulasso, Burkina Faso (Zongo I., personal communication); Kati, Mali and Boussé, Burkina Faso. Data points show malaria incidence defined as fever plus parasitaemia of any density or with a local defined parasite density cutoff, and are shown against the left vertical axis. All studies included children under 5 years of age, with the exception of the Kambila IPTc study, which included children under 10 years of age. For the Kambila IPTc study (Mali) the prevalence estimate at the start of the transmission season (92/262, 35.1%) was used rather than that measured at the end of the transmission season, as this was based on relatively small numbers (8/54, 15%). The curve shows the fitted relationship between all age incidence per annum and prevalence in children 2–10 years of age, 13 and is shown against the right vertical axis. Dashed lines show the upper and lower limit of the incidence-prevalence relationship defined by the IPTc data points.