INCONTROL INTENSITY FULL

Out-of-sample validation suggests that 742 (99%) of the 752 observed prevalence values were contained in the 95% CI for the posterior prediction.

INCONTROL INTENSITY FULL

Full details of the adequacy of model fit and out of sample predictive validity are presented in the appendix (pp 82–86). This small amount of data resulted in larger CIs for estimates arising in these countries ( appendix pp 67–68). Central African Republic, Congo, Djibouti, Equatorial Guinea, and Somalia, for example, had no available datapoints for 2000–18, whereas Guinea-Bissau and Lesotho had 50 or fewer datapoints in total over this period ( appendix pp 66–67). Countries where future sampling might need to be prioritised to allow for more precise estimates in the period leading up to the global targets are listed in the appendix (pp 66–68). Further geographical and temporal details of data and age profiles of the surveys are available in the appendix (pp 54–59).Įstimated uncertainty overall and by year is driven by underlying data density. Temporal coverage ranged from a minimum of 46 survey datapoints in 2000 to a maximum of 4860 datapoints (spanning 840 implementation units) in 2013. The 26 304 georeferenced datapoints, when aggregated by implementation unit, represent 5021 implementation unit-years of data covering 3096 (60%) of the 5183 implementation units. 24 496 datapoints (93%) were from studies conducted since 2005 and were based on quantification of eggs in stool using Kato-Katz ( appendix p 55) and, of the 12879 datapoints or surveys with a reported age range, 8588 (67%) were among children aged 5–14 years ( appendix pp 56–59). Methods Study design and participantsĪs of July 14, 2020, the ESPEN database contained 30 732 datapoints in sub-Saharan Africa, with 27 171 datapoints from between Jan 1, 2000, and (2236 datapoints had a missing year and 1325 were from before 2000), of which 26 304 (97%) could be geolocated to a specific coordinate or accurately assigned to a programmatic implementation unit ( appendix p 55). If elimination of soil-transmitted helminths as a public health problem is to be achieved by 2030, better resource allocation and renewed and increased investment in treatment and prevention activities are urgently required to accelerate reductions and ensure that no subpopulations are left behind. Our estimates can be used by national programmes and implementing partners to identify areas likely to require reassessment surveys, and areas that still require surveillance or intervention to better target preventive chemotherapy to children at high risk of morbidity and to enhance access to at least basic sanitation. Although the prevalence of soil-transmitted helminths has substantially reduced over the past two decades, with consideration of a revised control strategy warranted in many areas, it is still highly unlikely that all areas will achieve the global targets for 2020 and beyond. This space–time analysis quantifies progress towards elimination in 2000–18. We also include summaries for each country to increase the accessibility to and transparency of our estimates. Our model improves upon previous efforts by using a longitudinal perspective not included in earlier national or regional estimates, accounting for subnational variation in space–time, and including time-varying preventive chemotherapy, water and sanitation, and socioeconomic patterns. We estimate prevalence (with CIs) of infection, and of moderate-to-heavy intensity infection, for each soil-transmitted helminth species by implementation unit among children in 2000–18. We used a georeferenced database of soil-transmitted helminth prevalence for sub-Saharan Africa, to which we applied a Bayesian space–time model that included key time-varying determinants. This study provides estimates of the prevalence of moderate-to-heavy intensity soil-transmitted helminths at the implementation unit level to track progress toward the soil-transmitted helminth goals for 20 and help identify areas at highest risk of not attaining target thresholds.

The Lancet Regional Health – Western Pacific.

The Lancet Regional Health – Southeast Asia.

The Lancet Gastroenterology & Hepatology.

Incontrol intensity