Sitali L, Miller JM, Mwenda MC, Bridges DJ, Hawela MB, Hamainza B, Chizema-Kawesha E, Eisele TP, Chipeta J, Lindtjørn B: Distribution of Plasmodium species and assessment of performance of diagnostic tools used during a malaria survey in Southern and Western Provinces of Zambia. Malaria Journal 2019, 18:130.
Background Zambia continues to make strides in reducing malaria burden through the use of proven malaria interventions and has recently pledged to eliminate malaria by 2021. Case management services have been scaled up at community level with rapid diagnostic tests (RDTs) providing antigen-based detection of falciparum malaria only. Key to national malaria elimination goals is the ability to identify, treat and eliminate all Plasmodium species. This study sought to determine the distribution of non-falciparum malaria and assess the performance of diagnostic tests for Plasmodium falciparum in Western and Southern Provinces of Zambia, two provinces planned for early malaria elimination.
Methods A sub-set of individuals’ data and samples from a cross-sectional household survey, conducted during peak malaria transmission season in April and May 2017, was used. The survey collected socio-demographic information on household members and coverage of malaria interventions. Malaria testing was done on respondents of all ages using blood smears and RDTs while dried blood spots were collected on filter papers for analysis using photo-induced electron transfer polymerase chain reaction (PET-PCR). Slides were stained using Giemsa stain and examined by microscopy for malaria parasites.
Results From the 1567 individuals included, the overall prevalence of malaria was 19.4% (CI 17.5–21.4) by PCR, 19.3% (CI 17.4–21.4) by RDT and 12.9% (CI 11.3–14.7) by microscopy. Using PET-PCR as the gold standard, RDTs showed a sensitivity of 75.7% (CI 70.4–80.4) and specificity of 94.2% (CI 92.8–95.4). The positive predictive value (PPV) was 75.9% (CI 70.7–80.6) and negative predictive value (NPV) was 94.1% (CI 92.1–95.4). In contrast, microscopy for sensitivity, specificity, PPV, and NPV values were 56.9% (CI 51.1–62.5), 97.7% (CI 96.7–98.5), 85.6% (CI 80.0–90.2), 90.4% (CI 88.7–91.9), respectively. Non-falciparum infections were found only in Western Province, where 11.6% of P. falciparum infections were co-infections with Plasmodium ovale or Plasmodium malariae.
Conclusion From the sub-set of survey data analysed, non-falciparum species are present and occurred as mixed infections. As expected, PET-PCR was slightly more sensitive than both malaria RDTs and microscopy to detecting malaria infections.