gms | German Medical Science

53. Jahrestagung der Deutschen Gesellschaft für Medizinische Informatik, Biometrie und Epidemiologie e. V. (GMDS)

Deutsche Gesellschaft für Medizinische Informatik, Biometrie und Epidemiologie

15. bis 18.09.2008, Stuttgart

Human ecology of malaria in a highland endemic region in south western Kenya

Meeting Abstract

Suche in Medline nach

  • Sophia Githinji - University of Bonn, Bonn, Deutschland
  • Susanne Herbst - University of Bonn, Bonn, Deutschland
  • Thomas Kistemann - University of Bonn, Bonn, Deutschland

Deutsche Gesellschaft für Medizinische Informatik, Biometrie und Epidemiologie. 53. Jahrestagung der Deutschen Gesellschaft für Medizinische Informatik, Biometrie und Epidemiologie (gmds). Stuttgart, 15.-19.09.2008. Düsseldorf: German Medical Science GMS Publishing House; 2008. DocEPI1-5

Die elektronische Version dieses Artikels ist vollständig und ist verfügbar unter: http://www.egms.de/de/meetings/gmds2008/08gmds005.shtml

Veröffentlicht: 10. September 2008

© 2008 Githinji et al.
Dieser Artikel ist ein Open Access-Artikel und steht unter den Creative Commons Lizenzbedingungen (http://creativecommons.org/licenses/by-nc-nd/3.0/deed.de). Er darf vervielf&aauml;ltigt, verbreitet und &oauml;ffentlich zug&aauml;nglich gemacht werden, vorausgesetzt dass Autor und Quelle genannt werden.


Gliederung

Text

Introduction

After 60 years of the world’s commitment to combat malaria, the disease still remains a great scourge of mankind recording around three million deaths a year. In Kenya, since the late 1980s, malaria has re-emerged in the highland regions west of the rift valley spreading to fifteen districts classified as highland malaria epidemic zones. Economic, and social factors such as, migration, increased population density and settlement, land use changes and deforestation are likely to be influencing this trend. This study assesses interactions between human beings and their immediate micro-ecological environment with regard to malaria transmission in the study area.

Materials and Methods

Malaria patients visiting a local health care facility were randomly sampled. Each sampled case was matched with a control of the same age and sex. Both the cases and controls were visited in their households within a period not exceeding two weeks after their attendance at the health care facility. In total, 670 patients were visited between May and July 2007. The study period coincided with malaria peak season in the area. A standardised questionnaire comprising of 5 open ended and 83 close ended questions was administered to each case/control or the caretaker. Respondents were asked if any member of their household had travelled out side the study area during the last two weeks preceding the date of interview and whether any member travelled regularly outside the study area. A detailed spot check of the housing conditions and homestead surroundings was also done. Materials used to construct the houses were recorded together with any other risk factors associated with the type of house. Vegetation, topography, and water collection points were spot checked under the homestead surrounding.

Results

Variables were classified under; housing conditions, homestead surroundings and exposure factors. Conditional logistic regression grouped on the basis of matched pairs of cases and controls was done separately for each of three classifications of variables. In the housing conditions category, only three variables; wall cracks, presence of eaves and water stored in the house recorded a p-value of less than 0.25 [1]. Further analysis of these variables showed that eaves are associated with a statistically significant odds ratio of 1.7 increase of malaria incidence (Table1 [Tab. 1]).

In the Exposure category, being out at night registered an odds ratio of 1.8 increase of malaria incidence (Table 2 [Tab. 2]). Regular travel outside the study area also showed a statistically significant association with malaria incidence (Table 3 [Tab. 3]). In the homestead surroundings category, only presence of a living fence around the homestead recorded a p-value of less than 0.25. Further analysis, of this variable recorded a non significant p-value of 0.115.

Conclusion

According to these preliminary results, poor housing conditions increase the risk of malaria infection. Regular travel outside the study area and being outside in the night also contribute to malaria incidences in the area. The latter two factors are of particular importance as they are not likely to be addressed by the widely promoted control measures of Insecticide Treated Nets (ITN) and Indoor Residual Spraying (IRS).


References

1.
Hosmer DW, Lemeshow S. Applied Logistic Regression 2nd Edition. John Willey & Sons, Inc. 2000.