Assessment of molecular markers of anti-malarial drug resistance among children participating in a therapeutic efficacy study in western Kenya.

BACKGROUND: Anti-malarial drug resistance remains a major threat to global malaria control efforts. In Africa, Plasmodium falciparum remains susceptible to artemisinin-based combination therapy (ACT), but the emergence of resistant parasites in multiple countries in Southeast Asia and concerns over emergence and/or spread of resistant parasites in Africa warrants continuous monitoring. The World Health Organization recommends that surveillance for molecular markers of resistance be included within therapeutic efficacy studies (TES). The current study assessed molecular markers associated with resistance to Artemether-lumefantrine (AL) and Dihydroartemisinin-piperaquine (DP) from samples collected from children aged 6-59 months enrolled in a TES conducted in Siaya County, western Kenya from 2016 to 2017. METHODS: Three hundred and twenty-three samples collected pre-treatment (day-0) and 110 samples collected at the day of recurrent parasitaemia (up to day 42) were tested for the presence of drug resistance markers in the Pfk13 propeller domain, and the Pfmdr1 and Pfcrt genes by Sanger sequencing. Additionally, the Pfpm2 gene copy number was assessed by real-time polymerase chain reaction. RESULTS: No mutations previously associated with artemisinin resistance were detected in the Pfk13 propeller region. However, other non-synonymous mutations in the Pfk13 propeller region were detected. The most common mutation found on day-0 and at day of recurrence in the Pfmdr1 multidrug resistance marker was at codon 184F. Very few mutations were found in the Pfcrt marker (< 5%). Within the DP arm, all recrudescent cases (8 sample pairs) that were tested for Pfpm2 gene copy number had a single gene copy. None of the associations between observed mutations and treatment outcomes were statistically significant. CONCLUSION: The results indicate absence of Pfk13 mutations associated with parasite resistance to artemisinin in this area and a very high proportion of wild-type parasites for Pfcrt. Although the frequency of Pfmdr1 184F mutations was high in these samples, the association with treatment failure did not reach statistical significance. As the spread of artemisinin-resistant parasites remains a possibility, continued monitoring for molecular markers of ACT resistance is needed to complement clinical data to inform treatment policy in Kenya and other malaria-endemic regions.

Community-based intermittent mass testing and treatment for malaria in an area of high transmission intensity, western Kenya: development of study site infrastructure and lessons learned.

BACKGROUND: Malaria transmission is high in western Kenya and the asymptomatic infected population plays a significant role in driving the transmission. Mathematical modelling and simulation programs suggest that interventions targeting asymptomatic infections through mass testing and treatment (MTaT) or mass drug administration (MDA) have the potential to reduce malaria transmission when combined with existing interventions. OBJECTIVE: This paper describes the study site, capacity development efforts required, and lessons learned for implementing a multi-year community-based cluster-randomized controlled trial to evaluate the impact of MTaT for malaria transmission reduction in an area of high transmission in western Kenya. METHODS: The study partnered with Kenya's Ministry of Health (MOH) and other organizations on community sensitization and engagement to mobilize, train and deploy community health volunteers (CHVs) to deliver MTaT in the community. Within the health facilities, the study availed staff, medical and laboratory supplies and strengthened health information management system to monitor progress and evaluate impact of intervention. RESULTS: More than 80 Kenya MOH CHVs, 13 clinical officers, field workers, data and logistical staff were trained to carry out MTaT three times a year for 2 years in a population of approximately 90,000 individuals. A supply chain management was adapted to meet daily demands for large volumes of commodities despite the limitation of few MOH facilities having ideal storage conditions. Modern technology was adapted more to meet the needs of the high daily volume of collected data. CONCLUSIONS: In resource-constrained settings, large interventions require capacity building and logistical planning. This study found that investing in relationships with the communities, local governments, and other partners, and identifying and equipping the appropriate staff with the skills and technology to perform tasks are important factors for success in delivering an intervention like MTaT.

Socioeconomic health inequality in malaria indicators in rural western Kenya: evidence from a household malaria survey on burden and care-seeking behaviour.

BACKGROUND: Health inequality is a recognized barrier to achieving health-related development goals. Health-equality data are essential for evidence-based planning and assessing the effectiveness of initiatives to promote equity. Such data have been captured but have not always been analysed or used to manage programming. Health data were examined for microeconomic differences in malaria indices and associated malaria control initiatives in western Kenya. METHODS: Data was analysed from a malaria cross-sectional survey conducted in July 2012 among 2719 people in 1063 households in Siaya County, Kenya. Demographic factors, history of fever, malaria parasitaemia, malaria medication usage, insecticide-treated net (ITN) use and expenditure on malaria medications were collected. A composite socioeconomic status score was created using multiple correspondence analyses (MCA) of household assets; households were classified into wealth quintiles and dichotomized into poorest (lowest 3 quintiles; 60%) or less-poor (highest 2 quintiles; 40%). Prevalence rates were calculated using generalized linear modelling. RESULTS: Overall prevalence of malaria infection was 34.1%, with significantly higher prevalence in the poorest compared to less-poor households (37.5% versus 29.2%, adjusted prevalence ratio [aPR] 1.23; 95% CI = 1.08-1.41, p = 0.002). Care seeking (aPR = 0.95; 95% CI 0.87-1.04, p = 0.229), medication use (aPR = 0.94; 95% CI 0.87-1.00, p = 0.087) and ITN use (aPR = 0.96; 95% CI = 0.87-1.05, p = 0.397) were similar between households. Among all persons surveyed, 36.4% reported taking malaria medicines in the prior 2 weeks; 92% took artemether-lumefantrine, the recommended first-line malaria medication. In the poorest households, 4.9% used non-recommended medicines compared to 3.5% in less-poor (p = 0.332). Mean and standard deviation [SD] for expenditure on all malaria medications per person was US$0.38 [US$0.50]; the mean was US$0.35 [US$0.52] amongst the poorest households and US$0.40 [US$0.55] in less-poor households (p = 0.076). Expenditure on non-recommended malaria medicine was significantly higher in the poorest (mean US$1.36 [US$0.91]) compared to less-poor households (mean US$0.98 [US$0.80]; p = 0.039). CONCLUSIONS: Inequalities in malaria infection and expenditures on potentially ineffective malaria medication between the poorest and less-poor households were evident in rural western Kenya. Findings highlight the benefits of using MCA to assess and monitor the health-equity impact of malaria prevention and control efforts at the microeconomic level.