Evidence map›Paper›PMID 37829802›Full record

ArticleHeliyon2023

Model-based geostatistical design and analysis of prevalence for soil-transmitted helminths in Kenya: Results from ten-years of the Kenya national school-based deworming programme.

Collins Okoyo, Mark Minnery, Idah Orowe, Chrispin Owaga, Suzy J Campbell, Christin Wambugu, Nereah Olick, Jane Hagemann, Wyckliff P Omondi, Kate McCracken and 5 more

Abstract read
In one paragraph

Article in Heliyon, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
–field-weighted citation impact
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

6 citing papers in PubMed.

  1. Article
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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

15 authors.

Collins OkoyoSchool of Mathematics, University of Nairobi, Nairobi, Kenya.
Mark MinneryDeworm the World, Evidence Action, Washington DC, United States.
Idah OroweSchool of Mathematics, University of Nairobi, Nairobi, Kenya.
Chrispin OwagaDeworm the World, Evidence Action, Nairobi, Kenya.
Suzy J CampbellDeworm the World, Evidence Action, Washington DC, United States.
Christin WambuguDivision of Adolescent and School Health (DASH), Ministry of Health, Nairobi, Kenya.
Nereah OlickSchool Health, Nutrition and Meals Unit (SHNMU), Ministry of Education, Nairobi, Kenya.
Jane HagemannDeworm the World, Evidence Action, Washington DC, United States.
Wyckliff P OmondiDivision of Vector Borne and Neglected Tropical Diseases (DVBNTD), Ministry of Health, Nairobi, Kenya.
Kate McCrackenDeworm the World, Evidence Action, Washington DC, United States.
Antonio MontresorDepartment of Control of Neglected Tropical Diseases, World Health Organization, Geneva, Switzerland.
Graham F MedleyFaculty of Public Health and Policy, London School of Hygiene and Tropical Medicine (LSHTM), London, United Kingdom.
Claudio FronterreCentre for Health Informatics, Computing and Statistics (CHICAS), Lancaster Medical School, Lancaster University, Lancaster, United Kingdom.
Peter DiggleCentre for Health Informatics, Computing and Statistics (CHICAS), Lancaster Medical School, Lancaster University, Lancaster, United Kingdom.
Charles MwandawiroEastern and Southern Africa Centre of International Parasite Control (ESACIPAC), Kenya Medical Research Institute, Nairobi, Kenya.

Funding

World Health Organization 001
6 · The paper itself

Abstract

Background: Kenya is endemic for soil-transmitted helminths (STH) with over 6 million children in 27 counties currently at-risk. A national school-based deworming programme (NSBDP) was launched in 2012 with a goal to eliminate parasitic worms as a public health problem. This study used model-based geostatistical (MBG) approach to design and analyse the impact of the NSBDP and inform treatment strategy changes. Methods: A cross-sectional study was used to survey 200 schools across 27 counties in Kenya. The study design, school selection and analysis followed the MBG approach which incorporated historical data on treatment, morbidity and environmental covariates to efficiently predict the helminths prevalence in Kenya. Results: Overall, the NSBDP geographic area prevalence for any STH was estimated to sit between 2 % and <10 % with a high predictive probability of >0.999. Species-specific thresholds were between 2 % and <10 % for Conclusions: Based on the World Health Organization guidelines, STH treatment requirements can now be confidently refined. Ten counties may consider suspending treatment and implement appropriate surveillance system, while another 10 will require treatment once every two years, and the remaining seven will require treatment once every year.

Indexed as

GeostatisticsKenyaModel-based geostatisticsModellingNational school-based dewormingPrevalenceSoil-transmitted helminths

Identifiers

PMID37829802
PMCPMC10565763

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

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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.