Asymptomatic malaria infections represent a major challenge in malaria control and elimination in Africa. They are reservoirs of malaria parasite that can contribute to disease transmission. Therefore, identification and control of asymptomatic infections are important to make malaria elimination feasible. In this study, we investigated the extent and distribution of asymptomatic malaria in Western Kenya and examined how varying parasitemia affects performance of diagnostic methods including microscopy, conventional PCR, and quantitative PCR. In addition, we compared parasite prevalence rates and parasitemia levels with respect to topography and age in order to explore factors that influence malaria infection. Over 11,000 asymptomatic blood samples from children and adolescents up to 18 years old representing broad areas of Western Kenya were included. Quantitative PCR revealed the highest parasite positive rate among all methods and malaria prevalence in western Kenya varied widely from less than 1% to over 50%. A significantly lower parasitemia was detected in highland than in lowland samples and this contrast was also observed primarily among submicroscopic samples. Although we found no correlation between parasitemia level and age, individuals of younger age group (aged <14) showed significantly higher parasite prevalence. In the lowlands, individuals of aged 5-14 showed significantly higher prevalence than those under age 5. Our findings highlight the need for a more sensitive and time-efficient assay for asymptomatic malaria detection particularly in areas of low-transmission. Combining QPCR with microscopy can enhance the capacity of detecting submicroscopic asymptomatic malaria infections.

Antibodies directed against malaria parasites are easy and inexpensive to measure but remain an underused surveillance tool because of a lack of consensus on what to measure and how to interpret results. High-throughput screening of antibodies from well-characterized cohorts offers a means to substantially improve existing assays by rationally choosing the most informative sets of responses and analytical methods. Recent data suggest that high-resolution information on malaria exposure can be obtained from a small number of samples by measuring a handful of properly chosen antibody responses. In this review, we discuss how standardized multi-antibody assays can be developed and efficiently integrated into existing surveillance activities, with potential to greatly augment the breadth and quality of information available to direct and monitor malaria control and elimination efforts.

Background

Centers for Disease Control and Prevention miniature light traps (CDC-LT) baited with CO2 are a routine tool for adult mosquito sampling used in entomological surveys, and for monitoring and surveillance of disease vectors. The present study was aimed at evaluating the performance of baited and unbaited CDC-LT for indoor and outdoor trapping of endemic mosquito species in northwestern Thailand.

Methods

CDC-LT (n = 112) with and without dry ice baits were set both indoors and outdoors in 88 selected houses for stretches of 5 consecutive nights per month in 7 villages in Tha Song Yang district, Tak province between January 2011 and March 2013. Individual traps were repeatedly placed in the same location for a median of 6 (range 1-10) times. Mosquitoes were identified by morphological characteristics and classified into blood-fed, empty, male/female and gravid. Absolute mosquito numbers were converted to capture rates (i.e., mosquitoes per trap and year). Capture rates were compared using multilevel negative binomial regression to account for multiple trap placements and adjust for regional and seasonal differences.

Results

A total of 6,668 mosquitoes from 9 genera were collected from 576 individual CDC-LT placements. Culex was the predominant captured genus (46%), followed by anopheline mosquitoes (45%). Overall, CO2 baited traps captured significantly more Culex (especially Culex vishnui Theobald) and Anopheles mosquitoes per unit time (adjusted capture rate ratio (aCRR) 1.64 and 1.38, respectively). Armigeres spp. mosquitoes were trapped in outdoor traps with significantly higher frequency (aCRR: 1.50), whereas Aedes albopictus (Skuse) had a tendency to be trapped more frequently indoors (aCRR: 1.89, p = 0.07). Furthermore, capture rate ratios between CO2 baited and non-baited CDC-LT were significantly influenced by seasonality and indoor vs. outdoor trap placement.

Conclusion

The present study shows that CDC-LT with CO2 baiting capture significantly more Culex and Anopheles mosquitoes, some of which (e.g., Cx. vishnui, Cx. quinquefasciatus Say, An. minimus s.l. Theobald, An. maculatus s.l. Theobald) represent important disease vectors in Thailand. This study also shows significant differences in the capture efficiency of CDC-LT when placed indoors or outdoors and in different seasons. Our study thus provides important guidelines for more targeted future vector trapping studies on the Thai-Myanmar border, which is an important cross-border malaria transmission region in Thailand.

Understanding the epidemiological features and metrics of malaria in endemic populations is a key component to monitoring and quantifying the impact of current and past control efforts to inform future ones. The International Centers of Excellence for Malaria Research (ICEMR) has the opportunity to evaluate the impact of malaria control interventions across endemic regions that differ in the dominant Plasmodium species, mosquito vector species, resistance to antimalarial drugs and human genetic variants thought to confer protection from infection and clinical manifestations of plasmodia infection. ICEMR programs are conducting field studies at multiple sites with the aim of generating standardized surveillance data to improve the understanding of malaria transmission and to monitor and evaluate the impact of interventions to inform malaria control and elimination programs. In addition, these epidemiological studies provide a vast source of biological samples linked to clinical and environmental "meta-data" to support translational studies of interactions between the parasite, human host, and mosquito vector. Importantly, epidemiological studies at the ICEMR field sites are integrated with entomological studies, including the measurement of the entomological inoculation rate, human biting index, and insecticide resistance, as well as studies of parasite genetic diversity and antimalarial drug resistance.

Measurement of malaria specific antibody responses represents a practical and informative method for malaria control programs to assess recent exposure to infection. Technical advances in recombinant antigen production, serological screening platforms, and analytical methods have enabled the identification of several target antigens for laboratory based and point-of-contact tests. Questions remain as to how these serological assays can best be integrated into malaria surveillance activities to inform programmatic decision-making. This report synthesizes discussions from a convening at Institut Pasteur in Paris in June 2017 aimed at defining practical and informative use cases for serology applications and highlights five programmatic uses for serological assays including: documenting the absence of transmission; stratification of transmission; measuring the effect of interventions; informing a decentralized immediate response;  and testing and treating P. vivax hypnozoite carriers.

Purpose

The Maternal Malaria and Malnutrition (M3) initiative has pooled together 13 studies with the hope of improving understanding of malaria-nutrition interactions during pregnancy and to foster collaboration between nutritionists and malariologists.

Participants

Data were pooled on 14 635 singleton, live birth pregnancies from women who had participated in 1 of 13 pregnancy studies. The 13 studies cover 8 countries in Africa and Papua New Guinea in the Western Pacific conducted from 1996 to 2015.

Findings to date

Data are available at the time of antenatal enrolment of women into their respective parent study and at delivery. The data set comprises essential data such as malaria infection status, anthropometric assessments of maternal nutritional status, presence of anaemia and birth weight, as well as additional variables such gestational age at delivery for a subset of women. Participating studies are described in detail with regard to setting and primary outcome measures, and summarised data are available from each contributing cohort.

Future plans

This pooled birth cohort is the largest pregnancy data set to date to permit a more definite evaluation of the impact of plausible interactions between poor nutritional status and malaria infection in pregnant women on fetal growth and gestational length. Given the current comparative lack of large pregnancy cohorts in malaria-endemic settings, compilation of suitable pregnancy cohorts is likely to provide adequate statistical power to assess malaria-nutrition interactions, and could point towards settings where such interactions are most relevant. The M3 cohort may thus help to identify pregnant women at high risk of adverse outcomes who may benefit from tailored intensive antenatal care including nutritional supplements and alternative or intensified malaria prevention regimens, and the settings in which these interventions would be most effective.

Background

Four studies previously indicated that the effect of malaria infection during pregnancy on the risk of low birthweight (LBW; <2,500 g) may depend upon maternal nutritional status. We investigated this dependence further using a large, diverse study population.

Methods and findings

We evaluated the interaction between maternal malaria infection and maternal anthropometric status on the risk of LBW using pooled data from 14,633 pregnancies from 13 studies (6 cohort studies and 7 randomized controlled trials) conducted in Africa and the Western Pacific from 1996-2015. Studies were identified by the Maternal Malaria and Malnutrition (M3) initiative using a convenience sampling approach and were eligible for pooling given adequate ethical approval and availability of essential variables. Study-specific adjusted effect estimates were calculated using inverse probability of treatment-weighted linear and log-binomial regression models and pooled using a random-effects model. The adjusted risk of delivering a baby with LBW was 8.8% among women with malaria infection at antenatal enrollment compared to 7.7% among uninfected women (adjusted risk ratio [aRR] 1.14 [95% confidence interval (CI): 0.91, 1.42]; N = 13,613), 10.5% among women with malaria infection at delivery compared to 7.9% among uninfected women (aRR 1.32 [95% CI: 1.08, 1.62]; N = 11,826), and 15.3% among women with low mid-upper arm circumference (MUAC <23 cm) at enrollment compared to 9.5% among women with MUAC ≥ 23 cm (aRR 1.60 [95% CI: 1.36, 1.87]; N = 9,008). The risk of delivering a baby with LBW was 17.8% among women with both malaria infection and low MUAC at enrollment compared to 8.4% among uninfected women with MUAC ≥ 23 cm (joint aRR 2.13 [95% CI: 1.21, 3.73]; N = 8,152). There was no evidence of synergism (i.e., excess risk due to interaction) between malaria infection and MUAC on the multiplicative (p = 0.5) or additive scale (p = 0.9). Results were similar using body mass index (BMI) as an anthropometric indicator of nutritional status. Meta-regression results indicated that there may be multiplicative interaction between malaria infection at enrollment and low MUAC within studies conducted in Africa; however, this finding was not consistent on the additive scale, when accounting for multiple comparisons, or when using other definitions of malaria and malnutrition. The major limitations of the study included availability of only 2 cross-sectional measurements of malaria and the limited availability of ultrasound-based pregnancy dating to assess impacts on preterm birth and fetal growth in all studies.

Conclusions

Pregnant women with malnutrition and malaria infection are at increased risk of LBW compared to women with only 1 risk factor or none, but malaria and malnutrition do not act synergistically.