Heterogeneity in the prevalence of subclinical malaria, other co-infections and anemia among pregnant women in rural areas of Myanmar: a community-based longitudinal study.

BACKGROUND: Due to the low prevalence of clinically suspected malaria among pregnant women in Myanmar, little is known about its impact on mothers and newborns. Helminth and Human Immuno-deficiency Virus (HIV) co-infections cause anemia in pregnant women. This study assessed the prevalence of subclinical malaria and co-infections among pregnant women, and its association with adverse outcomes of pregnancy in the presence of infection. METHODS: A prospective longitudinal study was conducted in 12 villages in two townships in Myanmar between 2013 to 2015. A total of 752 pregnant women, with a mean age of 27 years, were enrolled and followed up once a month until six weeks after childbirth. Prevalence ratio was calculated in the multivariable analysis. RESULTS: The prevalence of subclinical malaria as measured by nested PCR was 5.7% for either P. falciparum or P. vivax, 2.7% prevalence of P. falciparum and 2.8% prevalence of P. vivax. Helminth infections were prevalent in 17% of women, and one woman with an HIV infection was found in our study. The burden of anemia was high, with an overall prevalence of 37% with or without helminth infection, 42% of the women were malaria positive and 43% had dual infections (both malaria and helminth). Only 11 abnormal pregnancy outcomes (7 stillbirths, 2 premature, 2 twins) were identified. Poisson regression showed that women in their first trimester had a 2.9 times higher rate of subclinical malaria compared to women in the third trimester (PR:2.9, 95%CI 1.19, 7.31, p = 0.019), women who were enrolled during the wet season were 2.5 times more likely to be malaria positive than the women enrolled in the dry season (PR: 2.5, 95%CI 1.27, 4.88, p = 0.008), and the malaria positivity rate decreased by 5% when increased in one year of woman's age (PR:0.95, 95%CI 0.91, 0.99, p = 0.02). In the multivariable regression, the age of respondents was the only significant factor associated with subclinical malaria in pregnancy. CONCLUSIONS: A comprehensive approach of integrating interventions for malaria, anemia, and helminths should be delivered during antenatal care services for pregnant women in rural areas of Myanmar.

A cross-sectional study of avian influenza A virus in Myanmar live bird markets: Detection of a newly introduced H9N2?

BACKGROUND: Zoonotic influenza surveillance in Myanmar is sparse, despite the risks of introduction of such viruses from neighboring countries that could impact the poultry industry and lead to spillover to humans. METHODS: In July and August 2019, our multi-institutional partnership conducted a One Health-oriented, cross-sectional surveillance (weekly for 3 weeks) for influenza A and influenza D viruses at the three largest live bird markets in Yangon, Myanmar. RESULTS: The 27 bioaerosols, 90 bird cage swabs, 90 bird oropharyngeals, and 90 human nasopharyngeal samples yielded molecular influenza A detections in 8 bioaerosols (30.0%), 16 bird cages (17.8%), 15 bird oropharyngeals (16.7%), and 1 human nasopharyngeal (1.1%) samples. No influenza D was detected. Seven of the influenza A virus detections were found to be subtype A/H9N2, and one human nasopharyngeal sample was found to be subtype A/H1pdm. Among all IAV-positive samples, three of the A/H9N2-positive samples yielded live viruses from egg culture and their whole genome sequences revealing they belonged to the G9/Y280 lineage of A/H9N2 viruses. Phylogenetic analyses showed that these A/H9N2 sequences clustered separately from A/H9N2 viruses that were previously detected in Myanmar, supporting the notion that A/H9N2 viruses similar to those seen in wider Southeast Asia may have been introduced to Myanmar on multiple occasions. CONCLUSIONS: These findings call for increased surveillance efforts in Myanmar to monitor for the introduction of novel influenza viruses in poultry, as well as possible reassortment and zoonotic virus transmission.

Understanding Spatiotemporal Human Mobility Patterns for Malaria Control Using a Multiagent Mobility Simulation Model.

BACKGROUND: More details about human movement patterns are needed to evaluate relationships between daily travel and malaria risk at finer scales. A multiagent mobility simulation model was built to simulate the movements of villagers between home and their workplaces in 2 townships in Myanmar. METHODS: An agent-based model (ABM) was built to simulate daily travel to and from work based on responses to a travel survey. Key elements for the ABM were land cover, travel time, travel mode, occupation, malaria prevalence, and a detailed road network. Most visited network segments for different occupations and for malaria-positive cases were extracted and compared. Data from a separate survey were used to validate the simulation. RESULTS: Mobility characteristics for different occupation groups showed that while certain patterns were shared among some groups, there were also patterns that were unique to an occupation group. Forest workers were estimated to be the most mobile occupation group, and also had the highest potential malaria exposure associated with their daily travel in Ann Township. In Singu Township, forest workers were not the most mobile group; however, they were estimated to visit regions that had higher prevalence of malaria infection over other occupation groups. CONCLUSIONS: Using an ABM to simulate daily travel generated mobility patterns for different occupation groups. These spatial patterns varied by occupation. Our simulation identified occupations at a higher risk of being exposed to malaria and where these exposures were more likely to occur.

Temporal Dynamics of Subclinical Malaria in Different Transmission Zones of Myanmar.

Countries in the Greater Mekong Subregion have committed to eliminate Plasmodium falciparum malaria by 2025. Subclinical malaria infections that can be detected by highly sensitive polymerase chain reaction (PCR) testing in asymptomatic individuals represent a potential impediment to this goal, although the extent to which these low-density infections contribute to transmission is unclear. To understand the temporal dynamics of subclinical malaria in this setting, a cohort of 2,705 participants from three epidemiologically distinct regions of Myanmar was screened for subclinical P. falciparum and P. vivax infection using ultrasensitive PCR (usPCR). Standard rapid diagnostic tests (RDTs) for P. falciparum were also performed. Individuals who tested positive for malaria by usPCR were followed for up to 12 weeks. Regression analysis was performed to estimate whether the baseline prevalence of infection and the count of repeated positive tests were associated with demographic, behavioral, and clinical factors. At enrollment, the prevalence of subclinical malaria infection measured by usPCR was 7.7% (1.5% P. falciparum monoinfection, 0.3% mixed P. falciparum and P. vivax, and 6.0% P. vivax monoinfection), while P. falciparum prevalence measured by RDT was just 0.2%. Prevalence varied by geography and was higher among older people and in those with outdoor exposure and travel. No difference was observed in either the prevalence or count of subclinical infection by time of year, indicating that even in low-endemicity areas, a reservoir of subclinical infection persists year-round. If low-density infections are shown to represent a significant source of transmission, identification of high-risk groups and locations may aid elimination efforts.

Malaria Exposure in Ann Township, Myanmar, as a Function of Land Cover and Land Use: Combining Satellite Earth Observations and Field Surveys.

Despite progress toward malaria elimination in the Greater Mekong Subregion, challenges remain owing to the emergence of drug resistance and the persistence of focal transmission reservoirs. Malaria transmission foci in Myanmar are heterogeneous and complex, and many remaining infections are clinically silent, rendering them invisible to routine monitoring. The goal of this research is to define criteria for easy-to-implement methodologies, not reliant on routine monitoring, that can increase the efficiency of targeted malaria elimination strategies. Studies have shown relationships between malaria risk and land cover and land use (LCLU), which can be mapped using remote sensing methodologies. Here we aim to explain malaria risk as a function of LCLU for five rural villages in Myanmar's Rakhine State. Malaria prevalence and incidence data were analyzed through logistic regression with a land use survey of ~1,000 participants and a 30-m land cover map. Malaria prevalence per village ranged from 5% to 20% with the overwhelming majority of cases being subclinical. Villages with high forest cover were associated with increased risk of malaria, even for villagers who did not report visits to forests. Villagers living near croplands experienced decreased malaria risk unless they were directly engaged in farm work. Finally, land cover change (specifically, natural forest loss) appeared to be a substantial contributor to malaria risk in the region, although this was not confirmed through sensitivity analyses. Overall, this study demonstrates that remotely sensed data contextualized with field survey data can be used to inform critical targeting strategies in support of malaria elimination.