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Spatial distribution and cluster analysis of retail drug shop characteristics and antimalarial behaviors as reported by private medicine retailers in western Kenya: informing future interventions.

Rusk A, Highfield L, Wilkerson JM, Harrell M, Obala A, Amick B - Int J Health Geogr (2016)

Bottom Line: A statistically significant cluster of fewer than expected pharmacy-trained retailers was found (RR = .09, p = .001) when compared to the expected random distribution.Spatial clustering was found in the data.A concerning amount of correlation was found in one specific region in the study area where multiple behaviors converged in space, highlighting a prime target for interventions.

View Article: PubMed Central - PubMed

Affiliation: The University of Texas School of Public Health, Pressler Dr, Houston, TX, USA. andriaerusk@gmail.com.

ABSTRACT

Background: Efforts to improve malaria case management in sub-Saharan Africa have shifted focus to private antimalarial retailers to increase access to appropriate treatment. Demands to decrease intervention cost while increasing efficacy requires interventions tailored to geographic regions with demonstrated need. Cluster analysis presents an opportunity to meet this demand, but has not been applied to the retail sector or antimalarial retailer behaviors. This research conducted cluster analysis on medicine retailer behaviors in Kenya, to improve malaria case management and inform future interventions.

Methods: Ninety-seven surveys were collected from medicine retailers working in the Webuye Health and Demographic Surveillance Site. Survey items included retailer training, education, antimalarial drug knowledge, recommending behavior, sales, and shop characteristics, and were analyzed using Kulldorff's spatial scan statistic. The Bernoulli purely spatial model for binomial data was used, comparing cases to controls. Statistical significance of found clusters was tested with a likelihood ratio test, using the hypothesis of no clustering, and a p value based on 999 Monte Carlo simulations. The hypothesis was rejected with p values of 0.05 or less.

Results: A statistically significant cluster of fewer than expected pharmacy-trained retailers was found (RR = .09, p = .001) when compared to the expected random distribution. Drug recommending behavior also yielded a statistically significant cluster, with fewer than expected retailers recommending the correct antimalarial medication to adults (RR = .018, p = .01), and fewer than expected shops selling that medication more often than outdated antimalarials when compared to random distribution (RR = 0.23, p = .007). All three of these clusters were co-located, overlapping in the northwest of the study area.

Conclusion: Spatial clustering was found in the data. A concerning amount of correlation was found in one specific region in the study area where multiple behaviors converged in space, highlighting a prime target for interventions. These results also demonstrate the utility of applying geospatial methods in the study of medicine retailer behaviors, making the case for expanding this approach to other regions.

No MeSH data available.


Related in: MedlinePlus

Detailed map of the study area with shop locations. Adapted from Smith et al. 2011 [50]
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Fig2: Detailed map of the study area with shop locations. Adapted from Smith et al. 2011 [50]

Mentions: These locations, referred to here as medicine retailers, make up the study population and include all outlets that are located up to or within 5 km of the WHDSS border with the exception of the river-bound north-eastern border, to include the retailers that are accessible to those living within the WHDSS. Locations that were included were privately owned and carried any antimalarial medication. Exclusion criteria included those retailers that sold only general goods, were public health facilities, or refused to participate in the survey. A map of the WHDSS, retail outlet locations, and major roadways can be seen in Fig. 2.Fig. 2


Spatial distribution and cluster analysis of retail drug shop characteristics and antimalarial behaviors as reported by private medicine retailers in western Kenya: informing future interventions.

Rusk A, Highfield L, Wilkerson JM, Harrell M, Obala A, Amick B - Int J Health Geogr (2016)

Detailed map of the study area with shop locations. Adapted from Smith et al. 2011 [50]
© Copyright Policy - OpenAccess
Related In: Results  -  Collection

License 1 - License 2
Show All Figures
getmorefigures.php?uid=PMC4759713&req=5

Fig2: Detailed map of the study area with shop locations. Adapted from Smith et al. 2011 [50]
Mentions: These locations, referred to here as medicine retailers, make up the study population and include all outlets that are located up to or within 5 km of the WHDSS border with the exception of the river-bound north-eastern border, to include the retailers that are accessible to those living within the WHDSS. Locations that were included were privately owned and carried any antimalarial medication. Exclusion criteria included those retailers that sold only general goods, were public health facilities, or refused to participate in the survey. A map of the WHDSS, retail outlet locations, and major roadways can be seen in Fig. 2.Fig. 2

Bottom Line: A statistically significant cluster of fewer than expected pharmacy-trained retailers was found (RR = .09, p = .001) when compared to the expected random distribution.Spatial clustering was found in the data.A concerning amount of correlation was found in one specific region in the study area where multiple behaviors converged in space, highlighting a prime target for interventions.

View Article: PubMed Central - PubMed

Affiliation: The University of Texas School of Public Health, Pressler Dr, Houston, TX, USA. andriaerusk@gmail.com.

ABSTRACT

Background: Efforts to improve malaria case management in sub-Saharan Africa have shifted focus to private antimalarial retailers to increase access to appropriate treatment. Demands to decrease intervention cost while increasing efficacy requires interventions tailored to geographic regions with demonstrated need. Cluster analysis presents an opportunity to meet this demand, but has not been applied to the retail sector or antimalarial retailer behaviors. This research conducted cluster analysis on medicine retailer behaviors in Kenya, to improve malaria case management and inform future interventions.

Methods: Ninety-seven surveys were collected from medicine retailers working in the Webuye Health and Demographic Surveillance Site. Survey items included retailer training, education, antimalarial drug knowledge, recommending behavior, sales, and shop characteristics, and were analyzed using Kulldorff's spatial scan statistic. The Bernoulli purely spatial model for binomial data was used, comparing cases to controls. Statistical significance of found clusters was tested with a likelihood ratio test, using the hypothesis of no clustering, and a p value based on 999 Monte Carlo simulations. The hypothesis was rejected with p values of 0.05 or less.

Results: A statistically significant cluster of fewer than expected pharmacy-trained retailers was found (RR = .09, p = .001) when compared to the expected random distribution. Drug recommending behavior also yielded a statistically significant cluster, with fewer than expected retailers recommending the correct antimalarial medication to adults (RR = .018, p = .01), and fewer than expected shops selling that medication more often than outdated antimalarials when compared to random distribution (RR = 0.23, p = .007). All three of these clusters were co-located, overlapping in the northwest of the study area.

Conclusion: Spatial clustering was found in the data. A concerning amount of correlation was found in one specific region in the study area where multiple behaviors converged in space, highlighting a prime target for interventions. These results also demonstrate the utility of applying geospatial methods in the study of medicine retailer behaviors, making the case for expanding this approach to other regions.

No MeSH data available.


Related in: MedlinePlus