Evidence map›Paper›PMID 33905476›Full record

ArticleClinical infectious diseases : an official publication of the Infectious Diseases Society of America2021

Model-Based Geostatistical Methods Enable Efficient Design and Analysis of Prevalence Surveys for Soil-Transmitted Helminth Infection and Other Neglected Tropical Diseases.

Olatunji Johnson, Claudio Fronterre, Benjamin Amoah, Antonio Montresor, Emanuele Giorgi, Nicholas Midzi, Masceline Jenipher Mutsaka-Makuvaza, Ibrahim Kargbo-Labor, Mary H Hodges, Yaobi Zhang and 4 more

Open access · hybridAbstract read
In one paragraph

Article in Clinical infectious diseases : an official publication of the Infectious Diseases Society of America, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
22citing papers in PubMed, 1 pooled it
4.1field-weighted citation impact, top 6% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

22 citing papers in PubMed, 1 synthesis or guideline pooled it, 31 citations in OpenAlex.

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  12. A Comparison of Markov and Mechanistic Models for Soil-Transmitted Helminth Prevalence Projections in the Context of Survey Design.Clinical infectious diseases : an official publication of the Infectious Diseases Society of America · 2024
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  14. Modernizing the design and analysis of prevalence surveys for neglected tropical diseases.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2023
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

14 authors at 7 institutions in 6 countries.

Olatunji JohnsonCentre for Health Informatics, Computing, and Statistics, Lancaster Medical School, Lancaster University, Lancaster, United Kingdom.
Claudio FronterreCentre for Health Informatics, Computing, and Statistics, Lancaster Medical School, Lancaster University, Lancaster, United Kingdom.
Benjamin AmoahCentre for Health Informatics, Computing, and Statistics, Lancaster Medical School, Lancaster University, Lancaster, United Kingdom.
Antonio MontresorDepartment of Control of Neglected Tropical Diseases, World Health Organization , Geneva, Switzerland.
Emanuele GiorgiCentre for Health Informatics, Computing, and Statistics, Lancaster Medical School, Lancaster University, Lancaster, United Kingdom.
Nicholas MidziNational Institute of Health Research, Ministry of Health and Child Care, Zimbabwe.
Masceline Jenipher Mutsaka-MakuvazaNational Institute of Health Research, Ministry of Health and Child Care, Zimbabwe.
Ibrahim Kargbo-LaborNeglected Tropical Disease Program, Ministry of Health and Sanitation, Freetown, Sierra Leone.
Mary H HodgesHelen Keller International, Regional Office for Africa, Dakar, Senegal.
Yaobi ZhangHelen Keller International, Regional Office for Africa, Dakar, Senegal.
Collins OkoyoEastern and Southern Africa Centre of International Parasite Control, Kenya Medical Research Institute, Nairobi, Kenya.
Charles MwandawiroEastern and Southern Africa Centre of International Parasite Control, Kenya Medical Research Institute, Nairobi, Kenya.
Mark MinneryDeworm the World, Evidence Action, Washington, District of Columbia, USA.
Peter J DiggleCentre for Health Informatics, Computing, and Statistics, Lancaster Medical School, Lancaster University, Lancaster, United Kingdom.
Lancaster University · GBHelen Keller International · USKenya Medical Research Institute · KEMinistry of Health and Child Welfare · ZWActionAid · USMinistry of Health and Sanitation · SLWorld Health Organization · CH

Funding

World Health Organization 001
6 · The paper itself

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.

Indexed as

HelminthiasisHelminthsAnimalsHumansKenyaNeglected DiseasesPrevalenceSierra LeoneSoilZimbabweSoilcontrol of neglected tropical diseasesgeospatial analysisimpact surveymodel-based geostatisticsprevalence surveysoil-transmitted helminth infection

Identifiers

PMID33905476
PMCPMC8201574
OpenAlexW3159384582

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.