Introduction: Africa currently uses Artemisinin-based combination therapy (ACT) as
recommended first-line treatment for uncomplicated malaria. Patients' adherence to ACT is an
important factor to ensure treatment efficacy, as well as to reduce the likelihood of parasite
resistance to these drugs. The adherence to ACTs, after the correct diagnosis can help in
reducing the unnecessary economic burden on antimalarials. The purpose of this study was to
determine patterns of antimalarial use and measure the level of use and the associated factors. It
aimed at making appropriate recommendations to reduce this level by addressing the associated
factors and through recommended policy changes. It is envisaged that it will reduce the
economic burden on antimalarials.
Methodology: This was a crosssectional descriptive study in which both qualitative and
quantitative methods of data collection were used. Qualitative method included focus group
discussions with purposively sampled group and indepth interviews with religious leaders,
herbalists and key community leaders for instance the subchief.
The quantitative involved a semi-structured pretested questionnaire administered to the head of
the randomly selected households by the interviewer. Study sub-locations were selected using a
multistage simple random sampling procedure and a systematic sampling procedure at the final
stage.
In the first stage, names of districts within Nairobi County were listed as obtained from KNBS,
2009 census. From this list Embakasi, Makadara, Lang’ata, and Westlands were selected
randomly by balloting. In the second stage, for each selected District, a list of all sub-locations
was made from which a proportionate number of sub-locations was randomly selected making a
total of sixteen sublocations.
From each sub-location a proportionate sample of household heads was made totaling to 402.
These were selected by systematic sampling technique. The pretesting of the questionnaire was
done in early June and data collection of data done in later June 2012 until early July.
Results: The level of antimalarial use was high (61.92%) in Nairobi. The Socio-demographic
factors were not found to contribute to this level, (gender, p=0.0293, marital status, p=0.007,
level of education, p=0.102, Employment status, p= 0.289 and income, p=0.080). The factors
that were found to have significant contribution through chi-square test included; duration after
onset of fever, p<0.001.
Prescriptions from the provider, p<0.007, place where antimalarials were bought, distance and
nature of source (Place, p<0.001, Nature of source, p= 0.041, distance, p=0.004), Source of
ACTs, p=0.047, Prior test for malaria and a positive test outcome, (Prior test, p<0.001, test
outcome, p=0.001) and finally people who had difficulties in completing the dose, p=0.013. The
other factors considered in this study if they had any significant association with antimalarial use
included self diagnosis by symptoms which had no association, p=0.433, respondents’
perception on level of malaria in Nairobi, which was found that majority perceived it to be low,
but antimalarial use was high, p=0.232, and cost of ACT, p=0.215 thus no association.
Regression analysis done on this factors which had shown significant association as independent
variables established that only the nearest source of antimalarial, was the only predictor of
antimalarial use. The nearest source of antimalarial which was a pharmacy/chemist at less than
5km had a very low odd ratio (OR= 0.022, 95% CI: 0.001-0.873).
Conclusion:
This study shows that the level of antimalarial use among the household heads in Nairobi County
is very high at 61.9%. This is much higher than the one observed in Malaria Indicator Survey
(MIS 2010) ranging from 33.3% to 39.7% in Children under five years in different age classes
and 43% in Khartoum state, Sudan(Awad et al.,2005). Socio-demographic factors such as age,
gender, marital status, education level, employment status and level income does not have a
statistical significant contribution to the level of antimalarial use.
The factors found associated with high antimalarial in this study included, duration after onset of
fever, prescription originating from health care providers, places where antimalarials were xiv
bought, including the nature of the nearest source and its distance. Prior malaria test, test
outcome and difficulty completing the dose were also found to contribute to antimalarial use.
Recommendations: Health education, on the true prevalence of malaria, causes and prevention
approaches to limit the use of antimalarials to only disserving cases is needed and training
through modules for specific providers of antimalarials especially the pharmacies and chemists
which play a big role in antimalarials provision. There is also need to develop and scale up
accessible and accurate testing sites with adequately trained staff for blood smear tests and rapid
diagnostic tests. Malaria being a major disease contributing immensely to morbidity and
mortality should have specific set aside clinics (Malaria Clinics) to encourage good practice
involving diagnosis, patient education on antimalarial use. Specific policies targeting areas of
presumed low risk like Nairobi to promote rational drug use should also be developed and
implemented.