Evaluation of point-of-care tests for cutaneous leishmaniasis diagnosis in Kabul, Afghanistan.

BACKGROUND: Kabul (Afghanistan) is a major focus of cutaneous leishmaniasis (CL) caused by Leishmania tropica. Microscopy remains the reference test for diagnosis despite its low performance. We evaluated whether Loopamp™ Leishmania Detection Kit (Loopamp) and CL Detect™ Rapid Test (CL Detect), detecting Leishmania DNA and antigen, respectively could improve CL diagnosis. METHODS: A diagnostic accuracy study with prospective inclusion was conducted in a leishmaniasis reference clinic in Kabul. Slit skin samples from CL suspects were analysed by microscopy. Samples taken with a dental broach were tested with CL Detect, Loopamp, and PCR. All samples were transferred to the Academic Medical Center (AMC, the Netherlands) for PCR and Loopamp analyses. The diagnostic performance of the tests was evaluated against a reference combining microscopy and PCR. FINDINGS: 274 CL suspects were included in the study. In Kabul, CL Detect had a 65·4% sensitivity [95% Confidence Interval (CI): 59.2-71.2%] and a 100% specificity [95% CI: 80.5-100%], while these were 87.6% [95%CI: 82.9-91.3%] and 70.6% [95% CI: 44.0-89.7%] for Loopamp. At AMC the Loopamp's sensitivity (92.2% [95% CI: 88.2-95.2%]) and specificity (94.1% [95% CI: 71.3-99.8%]) were higher. An algorithm where CL Detect negative suspects would be tested by Loopamp yielded a 93.4% sensitivity [95% CI: 89.6-96.1%] and a 94.1% specificity [95% CI: 71.3-99.8%] when Loopamp's performance at AMC was used. INTERPRETATION: The high specificity of CL Detect and the performance of Loopamp allow their use in a diagnostic algorithm that would minimize the number of CL patients referred for confirmation. FUND: Federal Ministry of Education and Research, Germany.

Modelling the incidence of Plasmodium vivax and Plasmodium falciparum malaria in Afghanistan 2006-2009.

BACKGROUND: Identifying areas that support high malaria risks and where populations lack access to health care is central to reducing the burden in Afghanistan. This study investigated the incidence of Plasmodium vivax and Plasmodium falciparum using routine data to help focus malaria interventions. METHODS: To estimate incidence, the study modelled utilisation of the public health sector using fever treatment data from the 2012 national Malaria Indicator Survey. A probabilistic measure of attendance was applied to population density metrics to define the proportion of the population within catchment of a public health facility. Malaria data were used in a Bayesian spatio-temporal conditional-autoregressive model with ecological or environmental covariates, to examine the spatial and temporal variation of incidence. FINDINGS: From the analysis of healthcare utilisation, over 80% of the population was within 2 hours' travel of the nearest public health facility, while 64.4% were within 30 minutes' travel. The mean incidence of P. vivax in 2009 was 5.4 (95% Crl 3.2-9.2) cases per 1000 population compared to 1.2 (95% Crl 0.4-2.9) cases per 1000 population for P. falciparum. P. vivax peaked in August while P. falciparum peaked in November. 32% of the estimated 30.5 million people lived in regions where annual incidence was at least 1 case per 1,000 population of P. vivax; 23.7% of the population lived in areas where annual P. falciparum case incidence was at least 1 per 1000. CONCLUSION: This study showed how routine data can be combined with household survey data to model malaria incidence. The incidence of both P. vivax and P. falciparum in Afghanistan remain low but the co-distribution of both parasites and the lag in their peak season provides challenges to malaria control in Afghanistan. Future improved case definition to determine levels of imported risks may be useful for the elimination ambitions in Afghanistan.