02510nas a2200277   4500000000100000008004100001260003400042653002300076653003100099653002300130653001700153653001800170100001200188700001500200700001400215700001500229700001400244700001700258700001500275245013500290856007400425300001400499490000700513520168700520022002502207       2024                            d  bOxford University Press (OUP)10aPrevalence surveys10aSoil-transmitted helminths10atransmission model10aMarkov model10ageostatistics1 aEyre MT1 aBulstra CA1 aJohnson O1 ade Vlas SJ1 aDiggle PJ1 aFronterrè C1 aCoffeng LE00aA Comparison of Markov and Mechanistic Models for Soil-Transmitted Helminth Prevalence Projections in the Context of Survey Design  uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC11045013/pdf/ciae022.pdf  aS146-S1520 v783 a<p>Globally, there are over 1 billion people infected with soil-transmitted helminths (STHs), mostly living in marginalized settings with inadequate sanitation in sub-Saharan Africa and Southeast Asia. The World Health Organization recommends an integrated approach to STH morbidity control through improved access to sanitation and hygiene education and the delivery of preventive chemotherapy (PC) to school-age children delivered through schools. Progress of STH control programs is currently estimated using a baseline (pre-PC) school-based prevalence survey and then monitored using periodical school-based prevalence surveys, known as Impact Assessment Surveys (IAS). We investigated whether integrating geostatistical methods with a Markov model or a mechanistic transmission model for projecting prevalence forward in time from baseline can improve IAS design strategies. To do this, we applied these 2 methods to prevalence data collected in Kenya, before evaluating and comparing their performance in accurately informing optimal survey design for a range of IAS sampling designs. We found that, although both approaches performed well, the mechanistic method more accurately projected prevalence over time and provided more accurate information for guiding survey design. Both methods performed less well in areas with persistent STH hotspots where prevalence did not decrease despite multiple rounds of PC. Our findings show that these methods can be useful tools for more efficient and accurate targeting of PC. The general framework built in this paper can also be used for projecting prevalence and informing survey design for other neglected tropical diseases.</p>
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