Optimising cluster survey design for planning schistosomiasis preventive chemotherapy.
The cornerstone of current schistosomiasis control programmes is delivery of praziquantel to at-risk populations. Such preventive chemotherapy requires accurate information on the geographic distribution of infection, yet the performance of alternative survey designs for estimating prevalence and co...
Main Authors: | , , , , , , , , , , , , , , , , |
---|---|
Format: | Article |
Language: | English |
Published: |
Public Library of Science (PLoS)
2017-05-01
|
Series: | PLoS Neglected Tropical Diseases |
Online Access: | http://europepmc.org/articles/PMC5464666?pdf=render |
id |
doaj-547b4dbac75c4f4eab29ac8441f3e8f0 |
---|---|
record_format |
Article |
spelling |
doaj-547b4dbac75c4f4eab29ac8441f3e8f02020-11-25T02:33:13ZengPublic Library of Science (PLoS)PLoS Neglected Tropical Diseases1935-27271935-27352017-05-01115e000559910.1371/journal.pntd.0005599Optimising cluster survey design for planning schistosomiasis preventive chemotherapy.Sarah C L KnowlesHugh J W SturrockHugo TurnerJane M WhittonCharlotte M GowerSamuel JemuAnna E PhillipsAboulaye MeiteBrent ThomasKarsor KollieCatherine ThomasMaria P RebolloBen StylesMichelle ClementsAlan FenwickWendy E HarrisonFiona M FlemingThe cornerstone of current schistosomiasis control programmes is delivery of praziquantel to at-risk populations. Such preventive chemotherapy requires accurate information on the geographic distribution of infection, yet the performance of alternative survey designs for estimating prevalence and converting this into treatment decisions has not been thoroughly evaluated.We used baseline schistosomiasis mapping surveys from three countries (Malawi, Côte d'Ivoire and Liberia) to generate spatially realistic gold standard datasets, against which we tested alternative two-stage cluster survey designs. We assessed how sampling different numbers of schools per district (2-20) and children per school (10-50) influences the accuracy of prevalence estimates and treatment class assignment, and we compared survey cost-efficiency using data from Malawi. Due to the focal nature of schistosomiasis, up to 53% simulated surveys involving 2-5 schools per district failed to detect schistosomiasis in low endemicity areas (1-10% prevalence). Increasing the number of schools surveyed per district improved treatment class assignment far more than increasing the number of children sampled per school. For Malawi, surveys of 15 schools per district and 20-30 children per school reliably detected endemic schistosomiasis and maximised cost-efficiency. In sensitivity analyses where treatment costs and the country considered were varied, optimal survey size was remarkably consistent, with cost-efficiency maximised at 15-20 schools per district.Among two-stage cluster surveys for schistosomiasis, our simulations indicated that surveying 15-20 schools per district and 20-30 children per school optimised cost-efficiency and minimised the risk of under-treatment, with surveys involving more schools of greater cost-efficiency as treatment costs rose.http://europepmc.org/articles/PMC5464666?pdf=render |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Sarah C L Knowles Hugh J W Sturrock Hugo Turner Jane M Whitton Charlotte M Gower Samuel Jemu Anna E Phillips Aboulaye Meite Brent Thomas Karsor Kollie Catherine Thomas Maria P Rebollo Ben Styles Michelle Clements Alan Fenwick Wendy E Harrison Fiona M Fleming |
spellingShingle |
Sarah C L Knowles Hugh J W Sturrock Hugo Turner Jane M Whitton Charlotte M Gower Samuel Jemu Anna E Phillips Aboulaye Meite Brent Thomas Karsor Kollie Catherine Thomas Maria P Rebollo Ben Styles Michelle Clements Alan Fenwick Wendy E Harrison Fiona M Fleming Optimising cluster survey design for planning schistosomiasis preventive chemotherapy. PLoS Neglected Tropical Diseases |
author_facet |
Sarah C L Knowles Hugh J W Sturrock Hugo Turner Jane M Whitton Charlotte M Gower Samuel Jemu Anna E Phillips Aboulaye Meite Brent Thomas Karsor Kollie Catherine Thomas Maria P Rebollo Ben Styles Michelle Clements Alan Fenwick Wendy E Harrison Fiona M Fleming |
author_sort |
Sarah C L Knowles |
title |
Optimising cluster survey design for planning schistosomiasis preventive chemotherapy. |
title_short |
Optimising cluster survey design for planning schistosomiasis preventive chemotherapy. |
title_full |
Optimising cluster survey design for planning schistosomiasis preventive chemotherapy. |
title_fullStr |
Optimising cluster survey design for planning schistosomiasis preventive chemotherapy. |
title_full_unstemmed |
Optimising cluster survey design for planning schistosomiasis preventive chemotherapy. |
title_sort |
optimising cluster survey design for planning schistosomiasis preventive chemotherapy. |
publisher |
Public Library of Science (PLoS) |
series |
PLoS Neglected Tropical Diseases |
issn |
1935-2727 1935-2735 |
publishDate |
2017-05-01 |
description |
The cornerstone of current schistosomiasis control programmes is delivery of praziquantel to at-risk populations. Such preventive chemotherapy requires accurate information on the geographic distribution of infection, yet the performance of alternative survey designs for estimating prevalence and converting this into treatment decisions has not been thoroughly evaluated.We used baseline schistosomiasis mapping surveys from three countries (Malawi, Côte d'Ivoire and Liberia) to generate spatially realistic gold standard datasets, against which we tested alternative two-stage cluster survey designs. We assessed how sampling different numbers of schools per district (2-20) and children per school (10-50) influences the accuracy of prevalence estimates and treatment class assignment, and we compared survey cost-efficiency using data from Malawi. Due to the focal nature of schistosomiasis, up to 53% simulated surveys involving 2-5 schools per district failed to detect schistosomiasis in low endemicity areas (1-10% prevalence). Increasing the number of schools surveyed per district improved treatment class assignment far more than increasing the number of children sampled per school. For Malawi, surveys of 15 schools per district and 20-30 children per school reliably detected endemic schistosomiasis and maximised cost-efficiency. In sensitivity analyses where treatment costs and the country considered were varied, optimal survey size was remarkably consistent, with cost-efficiency maximised at 15-20 schools per district.Among two-stage cluster surveys for schistosomiasis, our simulations indicated that surveying 15-20 schools per district and 20-30 children per school optimised cost-efficiency and minimised the risk of under-treatment, with surveys involving more schools of greater cost-efficiency as treatment costs rose. |
url |
http://europepmc.org/articles/PMC5464666?pdf=render |
work_keys_str_mv |
AT sarahclknowles optimisingclustersurveydesignforplanningschistosomiasispreventivechemotherapy AT hughjwsturrock optimisingclustersurveydesignforplanningschistosomiasispreventivechemotherapy AT hugoturner optimisingclustersurveydesignforplanningschistosomiasispreventivechemotherapy AT janemwhitton optimisingclustersurveydesignforplanningschistosomiasispreventivechemotherapy AT charlottemgower optimisingclustersurveydesignforplanningschistosomiasispreventivechemotherapy AT samueljemu optimisingclustersurveydesignforplanningschistosomiasispreventivechemotherapy AT annaephillips optimisingclustersurveydesignforplanningschistosomiasispreventivechemotherapy AT aboulayemeite optimisingclustersurveydesignforplanningschistosomiasispreventivechemotherapy AT brentthomas optimisingclustersurveydesignforplanningschistosomiasispreventivechemotherapy AT karsorkollie optimisingclustersurveydesignforplanningschistosomiasispreventivechemotherapy AT catherinethomas optimisingclustersurveydesignforplanningschistosomiasispreventivechemotherapy AT mariaprebollo optimisingclustersurveydesignforplanningschistosomiasispreventivechemotherapy AT benstyles optimisingclustersurveydesignforplanningschistosomiasispreventivechemotherapy AT michelleclements optimisingclustersurveydesignforplanningschistosomiasispreventivechemotherapy AT alanfenwick optimisingclustersurveydesignforplanningschistosomiasispreventivechemotherapy AT wendyeharrison optimisingclustersurveydesignforplanningschistosomiasispreventivechemotherapy AT fionamfleming optimisingclustersurveydesignforplanningschistosomiasispreventivechemotherapy |
_version_ |
1724815582857003008 |