Estimation of Malaria-Attributable Fever in Malaria Test-Positive Febrile Outpatients in Three Provinces of Mozambique, 2018

Laboratory Detection of Malaria Antigens: a Strong Tool for Malaria Research, Diagnosis, and Epidemiology

The identification and characterization of proteins produced during human infection with Plasmodium spp. have guided the malaria community in research, diagnosis, epidemiology, and other efforts. Recently developed methods for the detection of these proteins (antigens) in the laboratory have provided new types of data that can inform the evaluation of malaria diagnostics, epidemiological investigations, and overall malaria control strategies. Here, the focus is primarily on antigens that are currently known to be detectable in human specimens and on their impact on the understanding of malaria in human populations. We highlight historical and contemporary laboratory assays for malaria antigen detection, the concept of an antigen profile for a biospecimen, and ways in which binary results for a panel of antigens could be interpreted and utilized for different analyses. Particular emphasis is given to the direct comparison of field-level malaria diagnostics and laboratory antigen detection for the development of an external evaluation scheme. The current limitations of laboratory antigen detection are considered, and the future of this developing field is discussed.

Overdiagnosis of Malaria Illness in an Endemic Setting: A Facility-Based Surveillance Study in Malawi

In endemic settings where asymptomatic malaria infections are common, malaria infection can complicate fever diagnosis. Factors influencing fever misdiagnosis, including accuracy of malaria rapid diagnostic tests (mRDTs) and the malaria-attributable fraction of fevers (MAF), require further investigation. We conducted facility-based surveillance in Malawi, from January 2012 through December 2013 in settings of high perennial (Chikhwawa), high seasonal (Thoylo), and moderate seasonal (Ndirande) malaria transmission. Consecutive patients presenting to outpatient departments were screened; those with suspected malaria illness were tested by mRDT or routine thick-smear microscopy. Test positivity rates (TPRs), positive predictive value (PPVs) of mRDTs, and MAFs were calculated by site, age, and season. Of 41,471 patients, 10,052 (24.2%) tested positive for malaria. The TPR was significantly greater in Chikhwawa (29.9%; 95% CI, 28.6-30.0) compared with Thyolo (13.2%; 95% CI, 12.5-13.7) and Ndirande (13.1%; 95% CI, 12.2-14.4). The overall PPV was 77.8% (95% CI, 76.8-78.7); it was lowest among infants (69.9%; 95% CI, 65.5-74.2) and highest among school-age children (81.9%; 95% CI, 80.3-83.4). Malaria infection accounted for about 50% of fevers in children younger than 5 years old with microscopy-confirmed Plasmodium falciparum infection, and less than 20% of such fevers in school-age children. Outpatient settings in Malawi had a high burden of malaria illness, but also possible overdiagnosis of malaria illness. Interventions to reduce malaria transmission and rapid testing for other common febrile illness may improve diagnostic clarity among outpatients in malaria endemic settings.

Malaria micro-stratification using routine surveillance data in Western Kenya

BACKGROUND

There is an increasing need for finer spatial resolution data on malaria risk to provide micro-stratification to guide sub-national strategic plans. Here, spatial-statistical techniques are used to exploit routine data to depict sub-national heterogeneities in test positivity rate (TPR) for malaria among patients attending health facilities in Kenya.

METHODS

Routine data from health facilities (n = 1804) representing all ages over 24 months (2018-2019) were assembled across 8 counties (62 sub-counties) in Western Kenya. Statistical model-based approaches were used to quantify heterogeneities in TPR and uncertainty at fine spatial resolution adjusting for missingness, population distribution, spatial data structure, month, and type of health facility.

RESULTS

The overall monthly reporting rate was 78.7% (IQR 75.0-100.0) and public-based health facilities were more likely than private facilities to report ≥ 12 months (OR 5.7, 95% CI 4.3-7.5). There was marked heterogeneity in population-weighted TPR with sub-counties in the north of the lake-endemic region exhibiting the highest rates (exceedance probability > 70% with 90% certainty) where approximately 2.7 million (28.5%) people reside. At micro-level the lowest rates were in 14 sub-counties (exceedance probability < 30% with 90% certainty) where approximately 2.2 million (23.1%) people lived and indoor residual spraying had been conducted since 2017.

CONCLUSION

The value of routine health data on TPR can be enhanced when adjusting for underlying population and spatial structures of the data, highlighting small-scale heterogeneities in malaria risk often masked in broad national stratifications. Future research should aim at relating these heterogeneities in TPR with traditional community-level prevalence to improve tailoring malaria control activities at sub-national levels.

The relationship between facility-based malaria test positivity rate and community-based parasite prevalence

INTRODUCTION

Malaria surveillance is a key pillar in the control of malaria in Africa. The value of using routinely collected data from health facilities to define malaria risk at community levels remains poorly defined.

METHODS

Four cross-sectional parasite prevalence surveys were undertaken among residents at 36 enumeration zones in Kilifi county on the Kenyan coast and temporally and spatially matched to fever surveillance at 6 health facilities serving the same communities over 12 months. The age-structured functional form of the relationship between test positivity rate (TPR) and community-based parasite prevalence (PR) was explored through the development of regression models fitted by alternating the linear, exponential and polynomial terms for PR. The predictive ranges of TPR were explored for PR endemicity risk groups of control programmatic value using cut-offs of low (PR <5%) and high (PR ≥ 30%) transmission intensity.

RESULTS

Among 28,134 febrile patients encountered for malaria diagnostic testing in the health facilities, 12,143 (43.2%: 95% CI: 42.6%, 43.7%) were positive. The overall community PR was 9.9% (95% CI: 9.2%, 10.7%) among 6,479 participants tested for malaria. The polynomial model was the best fitting model for the data that described the algebraic relationship between TPR and PR. In this setting, a TPR of ≥ 49% in all age groups corresponded to an age-standardized PR of ≥ 30%, while a TPR of < 40% corresponded to an age-standardized PR of < 5%.

CONCLUSION

A non-linear relationship was observed between the relative change in TPR and changes in the PR, which is likely to have important implications for malaria surveillance programs, especially at the extremes of transmission. However, larger, more spatially diverse data series using routinely collected TPR data matched to community-based infection prevalence data are required to explore the more practical implications of using TPR as a replacement for community PR.

A Robust Estimator of Malaria Incidence from Routine Health Facility Data

Routine incident malaria case data have become a pillar of malaria surveillance in sub-Saharan Africa. These data provide granular, timely information to track malaria burden. However, incidence data are sensitive to changes in care seeking rates, rates of testing of suspect cases, and reporting completeness. Based on a set of assumptions, we derived a simple algebraic formula to convert crude incidence rates to a corrected estimation of incidence, adjusting for biases in variable and suboptimal rates of care seeking, testing of suspect cases, and reporting completeness. We applied the correction to routine incidence data from Guinea and Mozambique, and aggregate data for sub-Saharan African countries from the World Malaria Report. We calculated continent-wide needs for malaria tests and treatments, assuming universal testing but current care seeking rates. Countries in southern and eastern Africa reporting recent increases in malaria incidence generally had lower overall corrected incidence than countries in Central and West Africa. Under current care seeking rates, the unmet need for malaria tests was estimated to be 160 million (M) (interquartile range [IQR]: 139-188) and for malaria treatments to be 37 M (IQR: 29-51). Maps of corrected incidence were more consistent with maps of community survey prevalence than was crude incidence in Guinea and Mozambique. Crude malaria incidence rates need to be interpreted in the context of suboptimal testing and care seeking rates, which vary over space and time. Adjusting for these factors can provide insight into the spatiotemporal trends of malaria burden.