AI Article Synopsis

  • * It highlights the use of empirical data from local prevalence testing and digital environmental imagery to inform mapping efforts, especially in areas lacking comprehensive disease registries.
  • * Through case studies on soil-transmitted helminths in Kenya, Sierra Leone, and Zimbabwe, the article demonstrates that model-based geostatistics significantly outperforms current WHO guidelines in designing and analyzing prevalence surveys, indicating potential for improved mapping in other diseases.

Article Abstract

Maps of the geographical variation in prevalence play an important role in large-scale programs for the control of neglected tropical diseases. Precontrol mapping is needed to establish the appropriate control intervention in each area of the country in question. Mapping is also needed postintervention to measure the success of control efforts. In the absence of comprehensive disease registries, mapping efforts can be informed by 2 kinds of data: empirical estimates of local prevalence obtained by testing individuals from a sample of communities within the geographical region of interest, and digital images of environmental factors that are predictive of local prevalence. In this article, we focus on the design and analysis of impact surveys, that is, prevalence surveys that are conducted postintervention with the aim of informing decisions on what further intervention, if any, is needed to achieve elimination of the disease as a public health problem. We show that geospatial statistical methods enable prevalence surveys to be designed and analyzed as efficiently as possible so as to make best use of hard-won field data. We use 3 case studies based on data from soil-transmitted helminth impact surveys in Kenya, Sierra Leone, and Zimbabwe to compare the predictive performance of model-based geostatistics with methods described in current World Health Organization (WHO) guidelines. In all 3 cases, we find that model-based geostatistics substantially outperforms the current WHO guidelines, delivering improved precision for reduced field-sampling effort. We argue from experience that similar improvements will hold for prevalence mapping of other neglected tropical diseases.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8201574PMC
http://dx.doi.org/10.1093/cid/ciab192DOI Listing

Publication Analysis

Top Keywords

prevalence surveys
12
neglected tropical
12
tropical diseases
12
methods enable
8
design analysis
8
soil-transmitted helminth
8
mapping needed
8
local prevalence
8
impact surveys
8
model-based geostatistics
8

Similar Publications

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!