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Comparisons of predictors for typhoid and paratyphoid fever in Kolkata, India.

Sur D, Ali M, von Seidlein L, Manna B, Deen JL, Acosta CJ, Clemens JD, Bhattacharya SK - BMC Public Health (2007)

Bottom Line: We conducted a large enteric fever surveillance study and analyzed factors which correlate with enteric fever on an individual level and factors associated with high and low risk areas with enteric fever incidence.There was a close correlation between the characteristics detected based on individual cases and characteristics associated with high incidence areas.Because the comparison of risk factors of populations living in high versus low risk areas is statistically very powerful this methodology holds promise to detect risk factors associated with diseases using geographic information systems.

View Article: PubMed Central - HTML - PubMed

Affiliation: 1National Institute of Cholera and Enteric Diseases, Kolkata, India. dipikasur@hotmail.com

ABSTRACT

Background: Exposure of the individual to contaminated food or water correlates closely with the risk for enteric fever. Since public health interventions such as water improvement or vaccination campaigns are implemented for groups of individuals we were interested whether risk factors not only for the individual but for households, neighbourhoods and larger areas can be recognised?

Methods: We conducted a large enteric fever surveillance study and analyzed factors which correlate with enteric fever on an individual level and factors associated with high and low risk areas with enteric fever incidence. Individual level data were linked to a population based geographic information systems. Individual and household level variables were fitted in Generalized Estimating Equations (GEE) with the logit link function to take into account the likelihood that household factors correlated within household members.

Results: Over a 12-month period 80 typhoid fever cases and 47 paratyphoid fever cases were detected among 56,946 residents in two bustees (slums) of Kolkata, India. The incidence of paratyphoid fever was lower (0.8/1000/year), and the mean age of paratyphoid patients was older (17.1 years) than for typhoid fever (incidence 1.4/1000/year, mean age 14.7 years). Residents in areas with a high risk for typhoid fever had lower literacy rates and economic status, bigger household size, and resided closer to waterbodies and study treatment centers than residents in low risk areas.

Conclusion: There was a close correlation between the characteristics detected based on individual cases and characteristics associated with high incidence areas. Because the comparison of risk factors of populations living in high versus low risk areas is statistically very powerful this methodology holds promise to detect risk factors associated with diseases using geographic information systems.

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Related in: MedlinePlus

The location of the study area in Kolkata, India. The two referral hospitals of the typhoid program are shown in blue flags.
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Figure 1: The location of the study area in Kolkata, India. The two referral hospitals of the typhoid program are shown in blue flags.

Mentions: Kolkata is a densely populated mega-city with more than 13 million inhabitants, ranking among the top ten most populous cities of the world. About 40% of the population of Kolkata lives in bustees, officially designated slum areas. The city is divided into 141 administrative wards (Figure 1). The study site, Wards 29 and 30, was selected based on easy access from the research laboratory, the National Institute of Cholera and Enteric Diseases (NICED) and on the willingness of the community to participate in the study. The site is in eastern Kolkata, has a size of 0.99 km2 and is representative for many slum areas in the city.


Comparisons of predictors for typhoid and paratyphoid fever in Kolkata, India.

Sur D, Ali M, von Seidlein L, Manna B, Deen JL, Acosta CJ, Clemens JD, Bhattacharya SK - BMC Public Health (2007)

The location of the study area in Kolkata, India. The two referral hospitals of the typhoid program are shown in blue flags.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC2099435&req=5

Figure 1: The location of the study area in Kolkata, India. The two referral hospitals of the typhoid program are shown in blue flags.
Mentions: Kolkata is a densely populated mega-city with more than 13 million inhabitants, ranking among the top ten most populous cities of the world. About 40% of the population of Kolkata lives in bustees, officially designated slum areas. The city is divided into 141 administrative wards (Figure 1). The study site, Wards 29 and 30, was selected based on easy access from the research laboratory, the National Institute of Cholera and Enteric Diseases (NICED) and on the willingness of the community to participate in the study. The site is in eastern Kolkata, has a size of 0.99 km2 and is representative for many slum areas in the city.

Bottom Line: We conducted a large enteric fever surveillance study and analyzed factors which correlate with enteric fever on an individual level and factors associated with high and low risk areas with enteric fever incidence.There was a close correlation between the characteristics detected based on individual cases and characteristics associated with high incidence areas.Because the comparison of risk factors of populations living in high versus low risk areas is statistically very powerful this methodology holds promise to detect risk factors associated with diseases using geographic information systems.

View Article: PubMed Central - HTML - PubMed

Affiliation: 1National Institute of Cholera and Enteric Diseases, Kolkata, India. dipikasur@hotmail.com

ABSTRACT

Background: Exposure of the individual to contaminated food or water correlates closely with the risk for enteric fever. Since public health interventions such as water improvement or vaccination campaigns are implemented for groups of individuals we were interested whether risk factors not only for the individual but for households, neighbourhoods and larger areas can be recognised?

Methods: We conducted a large enteric fever surveillance study and analyzed factors which correlate with enteric fever on an individual level and factors associated with high and low risk areas with enteric fever incidence. Individual level data were linked to a population based geographic information systems. Individual and household level variables were fitted in Generalized Estimating Equations (GEE) with the logit link function to take into account the likelihood that household factors correlated within household members.

Results: Over a 12-month period 80 typhoid fever cases and 47 paratyphoid fever cases were detected among 56,946 residents in two bustees (slums) of Kolkata, India. The incidence of paratyphoid fever was lower (0.8/1000/year), and the mean age of paratyphoid patients was older (17.1 years) than for typhoid fever (incidence 1.4/1000/year, mean age 14.7 years). Residents in areas with a high risk for typhoid fever had lower literacy rates and economic status, bigger household size, and resided closer to waterbodies and study treatment centers than residents in low risk areas.

Conclusion: There was a close correlation between the characteristics detected based on individual cases and characteristics associated with high incidence areas. Because the comparison of risk factors of populations living in high versus low risk areas is statistically very powerful this methodology holds promise to detect risk factors associated with diseases using geographic information systems.

Show MeSH
Related in: MedlinePlus