Therapeutic efficacy of chloroquine and chloroquine plus primaquine for the treatment of Plasmodium vivax in Ethiopia.

Plasmodium vivax is the second most important cause of morbidity in Ethiopia. There is, however, little information on P. vivax resistance to chloroquine and chloroquine plus primaquine treatment although these drugs have been used as the first line treatment for over 50 years. We assessed the efficacy of standard chloroquine and chloroquine plus primaquine treatment for P. vivax infections in a randomized open-label comparative study in Debre Zeit and Nazareth in East Shoa, Ethiopia. A total of 290 patients with microscopically confirmed P. vivax malaria who presented to the outpatient settings of the two laboratory centers were enrolled: 145 patients were randomized to receive CQ and 145 to receive CQ+PQ treatment. Participants were followed-up for 28-157 days according to the WHO procedures. There were 12 (6.5%) lost to follow-up patients and 9 (3.1%) withdrawals. In all, 96% (277/290) of patients were analysed at day 28. Baseline characteristics were similar in all treatment groups. In all, 98.6% (275/277) of patients had cleared their parasitemia on day 3 with no difference in mean parasite clearance time between regimens (48.34+/-17.68, 50.67+/-15.70 h for the CQ and CQ+PQ group, respectively, P=0.25). The cumulative incidence of therapeutic failure at day 28 by a life-table analysis method was 5.76% (95% CI: 2.2-14.61) and 0.75% (95% CI: 0.11-5.2%) in the CQ and CQ+PQ group, respectively (P=0.19). The relapse rate was 8% (9/108) for the CQ group and 3% (4/132) for the comparison group (P=0.07). The cumulative risk of relapse at day 157 by a life-table method was 61.8% (95% CI: 20.1-98.4%) in the CQ group, compared with 26.3% (95% CI: 7.5-29.4%) in the CQ+PQ group (P=0.0038). The study confirms the emergence of CQ and PQ resistance/treatment failure in P. vivax malaria in Ethiopia. Although treatment failures were detected, they were similar between the treatment groups. We recommend regular monitoring and periodic evaluation of the efficacy of these antimalarial drugs in systematically selected sentinel sites to detect further development of resistance and to make timely national antimalarial drug policy changes.

Spatial analysis of malaria incidence at the village level in areas with unstable transmission in Ethiopia.

BACKGROUND: Malaria is the leading cause of morbidity and mortality in Ethiopia, accounting for over five million cases and thousands of deaths annually. The risks of morbidity and mortality associated with malaria are characterized by spatial and temporal variation across the country. This study examines the spatial and temporal patterns of malaria transmission at the local level and implements a risk mapping tool to aid in monitoring and disease control activities. METHODS: In this study, we examine the global and local patterns of malaria distribution in 543 villages in East Shoa, central Ethiopia using individual-level morbidity data collected from six laboratory and treatment centers between September 2002 and August 2006. RESULTS: Statistical analysis of malaria incidence by sex, age, and village through time reveal the presence of significant spatio-temporal variations. Poisson regression analysis shows a decrease in malaria incidence with increasing age. A significant difference in the malaria incidence density ratio (IDRs) is detected in males but not in females. A significant decrease in the malaria IDRs with increasing age is captured by a quadratic model. Local spatial statistics reveals clustering or hot spots within a 5 and 10 km distance of most villages in the study area. In addition, there are temporal variations in malaria incidence. CONCLUSION: Malaria incidence varies according to gender and age, with males age 5 and above showing a statistically higher incidence. Significant local clustering of malaria incidence occurs between pairs of villages within 1-10 km distance lags. Malaria incidence was higher in 2002-2003 than in other periods of observation. Malaria hot spots are displayed as risk maps that are useful for monitoring and spatial targeting of prevention and control measures against the disease.