Evidence map›Paper›PMID 27919235›Full record

ArticleBMC infectious diseases2016

Geographical distribution of typhoid risk factors in low and middle income countries.

Jung-Seok Lee, Vijayalaxmi V Mogasale, Vittal Mogasale, Kangsung Lee

Open access · goldAbstract read
In one paragraph

Article in BMC infectious diseases, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
34citing papers in PubMed, 2 pooled it
10.0field-weighted citation impact, top 2% 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

34 citing papers in PubMed, 2 syntheses or guidelines pooled it, 66 citations in OpenAlex.

  1. Risk Factors for Typhoid Fever: Systematic Review.JMIR public health and surveillance · 2025
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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

4 authors at 1 institution in 1 country.

Jung-Seok LeeInternational Vaccine Institute, SNU Research Park, 1 Gwanak-ro, Gwanack-gu, Seoul, South Korea. jslee@ivi.int.
Vijayalaxmi V MogasaleInternational Vaccine Institute, SNU Research Park, 1 Gwanak-ro, Gwanack-gu, Seoul, South Korea.
Vittal MogasaleInternational Vaccine Institute, SNU Research Park, 1 Gwanak-ro, Gwanack-gu, Seoul, South Korea.
Kangsung LeeInternational Vaccine Institute, SNU Research Park, 1 Gwanak-ro, Gwanack-gu, Seoul, South Korea.
International Vaccine Institute · KR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundWhile the global burden of typhoid fever has been often brought up for attention, the detailed surveillance information has only been available for the limited number of countries. As more efficacious vaccines will be available in the near future, it is essential to understand the geographically diverse patterns of typhoid risk levels and to prioritize the right populations for vaccination to effectively control the disease.

methodsA composite index called the typhoid risk factor (TRF) index was created based on data with the Global Positioning System (GPS). Demographic and Health Surveys (DHS) and National Geographical Data Center (NGDC) satellite lights data were used for this analysis. A count model was adopted to validate the TRF index against the existing surveillance burden data. The TRF index was then re-estimated for 66 countries using the most recent data and mapped out for two geographical levels (sub-national boundary and grid-cell levels).

resultsThe TRF index which consists of drinking water sources, toilet facility types, and population density appeared to be statistically significant to explain variation in the disease burden data. The mapping analysis showed that typhoid risk levels vary not only by country but also by sub-national region. The grid-cell level analysis highlighted that the distribution of typhoid risk factors is uneven within the sub-national boundary level. Typhoid risk levels are geographically heterogeneous.

conclusionsGiven the insufficient number of surveillance studies, the TRF index serves as a useful tool by capturing multiple risk factors of the disease into a single indicator. This will help decision makers identify high risk areas for typhoid as well as other waterborne diseases. Further, the study outcome can guide researchers to find relevant places for future surveillance studies.

Indexed as

GeographyHumansIncomeRisk FactorsTyphoid FeverComposite indexDisease mappingRisk factorsTyphoid

Identifiers

PMID27919235
PMCPMC5139008
OpenAlexW2559763874

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.