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.

Antibody signatures of asymptomatic Plasmodium falciparum malaria infections measured from dried blood spots.

BACKGROUND: Screening malaria-specific antibody responses on protein microarrays can help identify immune factors that mediate protection against malaria infection, disease, and transmission, as well as markers of past exposure to both malaria parasites and mosquito vectors. Most malaria protein microarray work has used serum as the sample matrix, requiring prompt laboratory processing and a continuous cold chain, thus limiting applications in remote locations. Dried blood spots (DBS) pose minimal biohazard, do not require immediate laboratory processing, and are stable at room temperature for transport, making them potentially superior alternatives to serum. The goals of this study were to assess the viability of DBS as a source for antibody profiling and to use DBS to identify serological signatures of low-density Plasmodium falciparum infections in malaria-endemic regions of Myanmar. METHODS: Matched DBS and serum samples from a cross-sectional study in Ingapu Township, Myanmar were probed on protein microarrays populated with P. falciparum antigen fragments. Signal and trends in both sample matrices were compared. A case-control study was then performed using banked DBS samples from malaria-endemic regions of Myanmar, and a regularized logistic regression model was used to identify antibody signatures of ultrasensitive PCR-positive P. falciparum infections. RESULTS: Approximately 30% of serum IgG activity was recovered from DBS. Despite this loss of antibody activity, antigen and population trends were well-matched between the two sample matrices. Responses to 18 protein fragments were associated with the odds of asymptomatic P. falciparum infection, albeit with modest diagnostic characteristics (sensitivity 58%, specificity 85%, negative predictive value 88%, and positive predictive value 52%). CONCLUSIONS: Malaria-specific antibody responses can be reliably detected, quantified, and analysed from DBS, opening the door to serological studies in populations where serum collection, transport, and storage would otherwise be impossible. While test characteristics of antibody signatures were insufficient for individual diagnosis, serological testing may be useful for identifying exposure to asymptomatic, low-density malaria infections, particularly if sero-surveillance strategies target individuals with low previous exposure as sentinels for population exposure.

A novel method for extracting nucleic acids from dried blood spots for ultrasensitive detection of low-density Plasmodium falciparum and Plasmodium vivax infections.

BACKGROUND: Greater Mekong Subregion countries are committed to eliminating Plasmodium falciparum malaria by 2025. Current elimination interventions target infections at parasite densities that can be detected by standard microscopy or rapid diagnostic tests (RDTs). More sensitive detection methods have been developed to detect lower density "asymptomatic" infections that may represent an important transmission reservoir. These ultrasensitive polymerase chain reaction (usPCR) tests have been used to identify target populations for mass drug administration (MDA). To date, malaria usPCR tests have used either venous or capillary blood sampling, which entails complex sample collection, processing and shipping requirements. An ultrasensitive method performed on standard dried blood spots (DBS) would greatly facilitate the molecular surveillance studies needed for targeting elimination interventions. METHODS: A highly sensitive method for detecting Plasmodium falciparum and P. vivax 18S ribosomal RNA from DBS was developed by empirically optimizing nucleic acid extraction conditions. The limit of detection (LoD) was determined using spiked DBS samples that were dried and stored under simulated field conditions. Further, to assess its utility for routine molecular surveillance, two cross-sectional surveys were performed in Myanmar during the wet and dry seasons. RESULTS: The lower LoD of the DBS-based ultrasensitive assay was 20 parasites/mL for DBS collected on Whatman 3MM filter paper and 23 parasites/mL for Whatman 903 Protein Saver cards-equivalent to 1 parasite per 50 µL DBS. This is about 5000-fold more sensitive than standard RDTs and similar to the LoD of ≤16-22 parasites/mL reported for other ultrasensitive methods based on whole blood. In two cross-sectional surveys in Myanmar, nearly identical prevalence estimates were obtained from contemporaneous DBS samples and capillary blood samples collected during the wet and dry season. CONCLUSIONS: The DBS-based ultrasensitive method described in this study shows equal sensitivity as previously described methods based on whole blood, both in its limit of detection and prevalence estimates in two field surveys. The reduced cost and complexity of this method will allow for the scale-up of surveillance studies to target MDA and other malaria elimination interventions, and help lead to a better understanding of the epidemiology of low-density malaria infections.

An ultrasensitive reverse transcription polymerase chain reaction assay to detect asymptomatic low-density Plasmodium falciparum and Plasmodium vivax infections in small volume blood samples.

BACKGROUND: Highly sensitive, scalable diagnostic methods are needed to guide malaria elimination interventions. While traditional microscopy and rapid diagnostic tests (RDTs) are suitable for the diagnosis of symptomatic malaria infection, more sensitive tests are needed to screen for low-density, asymptomatic infections that are targeted by interventions aiming to eliminate the entire reservoir of malaria infection in humans. METHODS: A reverse transcription polymerase chain reaction (RT- PCR) was developed for multiplexed detection of the 18S ribosomal RNA gene and ribosomal RNA of Plasmodium falciparum and Plasmodium vivax. Simulated field samples stored for 14 days with sample preservation buffer were used to assess the analytical sensitivity and specificity. Additionally, 1750 field samples from Southeastern Myanmar were tested both by RDT and ultrasensitive RT-PCR. RESULTS: Limits of detection (LoD) were determined under simulated field conditions. When 0.3 mL blood samples were stored for 14 days at 28 °C and 80% humidity, the LoD was less than 16 parasites/mL for P. falciparum and 19.7 copies/µL for P. vivax (using a plasmid surrogate), about 10,000-fold lower than RDTs. Of the 1739 samples successfully evaluated by both ultrasensitive RT-PCR and RDT, only two were RDT positive while 24 were positive for P. falciparum, 108 were positive for P. vivax, and 127 were positive for either P. vivax and/or P. falciparum using ultrasensitive RT-PCR. CONCLUSIONS: This ultrasensitive RT-PCR method is a robust, field-tested screening method that is vastly more sensitive than RDTs. Further optimization may result in a truly scalable tool suitable for widespread surveillance of low-level asymptomatic P. falciparum and P. vivax parasitaemia.

High-resolution hybrid micro-CT imaging pipeline for mouse brain region segmentation and volumetric morphometry.

BACKGROUND: Brain region segmentation and morphometry in humanized apolipoprotein E (APOE) mouse models with a human NOS2 background (HN) contribute to Alzheimer's disease (AD) research by demonstrating how various risk factors affect the brain. Photon-counting detector (PCD) micro-CT provides faster scan times than MRI, with superior contrast and spatial resolution to energy-integrating detector (EID) micro-CT. This paper presents a pipeline for mouse brain imaging, segmentation, and morphometry from PCD micro-CT. METHODS: We used brains of 26 mice from 3 genotypes (APOE22HN, APOE33HN, APOE44HN). The pipeline included PCD and EID micro-CT scanning, hybrid (PCD and EID) iterative reconstruction, and brain region segmentation using the Small Animal Multivariate Brain Analysis (SAMBA) tool. We applied SAMBA to transfer brain region labels from our new PCD CT atlas to individual PCD brains via diffeomorphic registration. Region-based and voxel-based analyses were used for comparisons by genotype and sex. RESULTS: Together, PCD and EID scanning take ~5 hours to produce images with a voxel size of 22 µm, which is faster than MRI protocols for mouse brain morphometry with voxel size above 40 µm. Hybrid iterative reconstruction generates PCD images with minimal artifacts and higher spatial resolution and contrast than EID images. Our PCD atlas is qualitatively and quantitatively similar to the prior MRI atlas and successfully transfers labels to PCD brains in SAMBA. Male and female mice had significant volume differences in 26 regions, including parts of the entorhinal cortex and cingulate cortex. APOE22HN brains were larger than APOE44HN brains in clusters from the hippocampus, a region where atrophy is associated with AD. CONCLUSIONS: This work establishes a pipeline for mouse brain analysis using PCD CT, from staining to imaging and labeling brain images. Our results validate the effectiveness of the approach, setting a foundation for research on AD mouse models while reducing scanning durations.

APOE, Immune Factors, Sex, and Diet Interact to Shape Brain Networks in Mouse Models of Aging.

Alzheimer's disease (AD) presents complex challenges due to its multifactorial nature, poorly understood etiology, and late detection. The mechanisms through which genetic, fixed and modifiable risk factors influence susceptibility to AD are under intense investigation, yet the impact of unique risk factors on brain networks is difficult to disentangle, and their interactions remain unclear. To model multiple risk factors including APOE genotype, age, sex, diet, and immunity we leveraged mice expressing the human APOE and NOS2 genes, conferring a reduced immune response compared to mouse Nos2. Employing graph analyses of brain connectomes derived from accelerated diffusion-weighted MRI, we assessed the global and local impact of risk factors in the absence of AD pathology. Aging and a high-fat diet impacted extensive networks comprising AD-vulnerable regions, including the temporal association cortex, amygdala, and the periaqueductal gray, involved in stress responses. Sex impacted networks including sexually dimorphic regions (thalamus, insula, hypothalamus) and key memory-processing areas (fimbria, septum). APOE genotypes modulated connectivity in memory, sensory, and motor regions, while diet and immunity both impacted the insula and hypothalamus. Notably, these risk factors converged on a circuit comprising 63 of 54,946 total connections (0.11% of the connectome), highlighting shared vulnerability amongst multiple AD risk factors in regions essential for sensory integration, emotional regulation, decision making, motor coordination, memory, homeostasis, and interoception. These network-based biomarkers hold translational value for distinguishing high-risk versus low-risk participants at preclinical AD stages, suggest circuits as potential therapeutic targets, and advance our understanding of network fingerprints associated with AD risk. Significance Statement: Current interventions for Alzheimer's disease (AD) do not provide a cure, and are delivered years after neuropathological onset. Addressing the impact of risk factors on brain networks holds promises for early detection, prevention, and revealing putative therapeutic targets at preclinical stages. We utilized six mouse models to investigate the impact of factors, including APOE genotype, age, sex, immunity, and diet, on brain networks. Large structural connectomes were derived from high resolution compressed sensing diffusion MRI. A highly parallelized graph classification identified subnetworks associated with unique risk factors, revealing their network fingerprints, and a common network composed of 63 connections with shared vulnerability to all risk factors. APOE genotype specific immune signatures support the design of interventions tailored to risk profiles.

Brain network fingerprints of Alzheimer's disease risk factors in mouse models with humanized APOE alleles.

Alzheimer's disease (AD) presents complex challenges due to its multifactorial nature, poorly understood etiology, and late detection. The mechanisms through which genetic and modifiable risk factors influence disease susceptibility are under intense investigation, with APOE being the major genetic risk factor for late onset AD. Yet the impact of unique risk factors on brain networks is difficult to disentangle, and their interactions remain unclear. To model multiple risk factors, including APOE genotype, age, sex, diet, and immunity we used a cross sectional design, leveraging mice expressing human APOE and NOS2 genes, conferring a reduced immune response compared to mouse Nos2. We used network topological and GraphClass analyses of brain connectomes derived from accelerated diffusion-weighted MRI to assess the global and local impact of risk factors, in the absence of AD pathology. Aging and a high-fat diet impacted extensive networks comprising AD-vulnerable regions, including the temporal association cortex, amygdala, and the periaqueductal gray, involved in stress responses. Sex impacted networks including sexually dimorphic regions (thalamus, insula, hypothalamus) and key memory-processing areas (fimbria, septum). APOE genotypes modulated connectivity in memory, sensory, and motor regions, while diet and immunity both impacted the insula and hypothalamus. Notably, these risk factors converged on a circuit comprising 63 of 54,946 total connections (0.11% of the connectome), highlighting shared vulnerability amongst multiple AD risk factors in regions essential for sensory integration, emotional regulation, decision making, motor coordination, memory, homeostasis, and interoception. APOE genotype specific immune signatures support the design of interventions tailored to risk profiles. Sparse Canonical Correlation Analysis (CCA) including spatial memory as a risk factor resulted in a network comprising 80 edges, showing significant overlap with risk-associated networks from GraphClass. The largest overlaps were observed with networks impacted by diet (47 edges), immunity (39 edges), APOE3 vs 4 (26 edges), sex (23 edges), and age (19 edges), the resulting networks supporting the use of sensory cues in spatial memory retrieval. These network-based biomarkers hold translational value for distinguishing high-risk versus low-risk participants at preclinical AD stages, suggest circuits as potential therapeutic targets, and advance our understanding of network fingerprints associated with AD risk.

Multivariate investigation of aging in mouse models expressing the Alzheimer's protective APOE2 allele: integrating cognitive metrics, brain imaging, and blood transcriptomics.

APOE allelic variation is critical in brain aging and Alzheimer's disease (AD). The APOE2 allele associated with cognitive resilience and neuroprotection against AD remains understudied. We employed a multipronged approach to characterize the transition from middle to old age in mice with APOE2 allele, using behavioral assessments, image-derived morphometry and diffusion metrics, structural connectomics, and blood transcriptomics. We used sparse multiple canonical correlation analyses (SMCCA) for integrative modeling, and graph neural network predictions. Our results revealed brain sub-networks associated with biological traits, cognitive markers, and gene expression. The cingulate cortex emerged as a critical region, demonstrating age-associated atrophy and diffusion changes, with higher fractional anisotropy in males and middle-aged subjects. Somatosensory and olfactory regions were consistently highlighted, indicating age-related atrophy and sex differences. The hippocampus exhibited significant volumetric changes with age, with differences between males and females in CA3 and CA1 regions. SMCCA underscored changes in the cingulate cortex, somatosensory cortex, olfactory regions, and hippocampus in relation to cognition and blood-based gene expression. Our integrative modeling in aging APOE2 carriers revealed a central role for changes in gene pathways involved in localization and the negative regulation of cellular processes. Our results support an important role of the immune system and response to stress. This integrative approach offers novel insights into the complex interplay among brain connectivity, aging, and sex. Our study provides a foundation for understanding the impact of APOE2 allele on brain aging, the potential for detecting associated changes in blood markers, and revealing novel therapeutic intervention targets.

Comparison of deforestation and forest land use factors for malaria elimination in Myanmar.

Objectives: Within the remote region of Ann Township in Myanmar's Rakhine State, malaria prevalence has remained steady at ∼10% of the population from 2016-2019. Previous studies have linked areas of higher malaria prevalence in the region to heavily forested areas, however, little is known about how people live, work, and move through these areas. This work aims to disentangle landscape from land use in regard to malaria exposure. Methods: We investigated the roles of forest cover, forest loss, and land use activities with malaria prevalence through the combined use of land use surveys, malaria surveillance, and satellite earth observations. Results: Our results confirm previous research that linked areas of high forest cover with high malaria prevalence. However, areas experiencing high levels of deforestation were not associated with malaria prevalence. The land use factors that contribute most significantly to increased malaria risk remained those which put people in direct contact with forests, including conducting forest chores, having an outdoor job, and having a primary occupation in the logging and/or plantation industry. Conclusion: Malaria prevention methods in Myanmar should focus on anyone who lives near forests or engages in land use activities that bring them within proximity of forested landscapes, whether through occupation or chores.

Developing Molecular Surveillance Capacity for Asymptomatic and Drug-Resistant Malaria in a Resource-Limited Setting-Experiences and Lessons Learned.

The COVID-19 pandemic has highlighted the important role molecular surveillance plays in public health. Such capacity however is either weak or nonexistent in many low-income countries. This article outlines a 2-year effort to establish two high-throughput molecular surveillance laboratories in Myanmar for tracking asymptomatic and drug resistant Plasmodium falciparum malaria. The lessons learned from this endeavor may prove useful for others seeking to establish similar molecular surveillance capacity in other resource-limited settings.

G6PD deficiency among malaria-infected national groups at the western part of Myanmar with implications for primaquine use in malaria elimination.

BACKGROUND: Glucose 6-phosphate dehydrogenase deficiency (G6PDd) plays a central role in readiness assessment for malaria elimination in Myanmar by 2030 that includes primaquine (PQ) use. The risk of hemolysis in G6PDd individuals hampers the widespread use of primaquine safely in malaria-infected patients. In the pre-elimination era, it is important to screen initially for asymptomatic malaria in combination with G6PD deficiency by applying more sensitive diagnostic tools. Therefore, this study examined the proportion of G6PDd and the distribution of G6PD genotypes among malaria-infected national groups in Myanmar before initiation of malaria elimination strategies. METHODS: A cross-sectional study in one township each with high malaria burden from two states in the western part of Myanmar, was conducted during 2016-2018, and 320 participants (164 Rakhine and 156 Chin National groups) were recruited. We used RDT and ultrasensitive polymerase chain reaction (us PCR) method to confirm malaria infection, and a G6PD RDT(CareStart) to detect G6PDd and PCR/restriction fragment length polymorphism (RFLP) method to confirm the variant of G6PDd for genotyping. G6PD enzyme activity was measured by G6PD Biosensor (CareStart). RESULTS: Malaria positivity rates detected by RDT were lower than those detected by us PCR in the combined samples [13% (42/320) vs. 21% (67/320)] as well as in the Rakhine samples [17% (28/164) vs. 25% (41/164)] and in Chin samples [9% (14/156) vs. 17% (26/156)]. G6PD deficiency rates were approximately 10% in both the combined samples and specific national groups. For G6PD enzyme activity in the combined samples, G6PDd (defined as < 30% of adjusted male median) was 10% (31/320) and severe G6PDd (< 10% of AMM) was 3% (9/320). Among malaria-infected patients with positive by both RDT and usPCR, G6PDd was less than 20% in each national group. G6PD genotyping showed that the G6PD Mahidol (G487A) was the major variant. CONCLUSIONS: The varying degree of G6PDd detected among malaria-infected national groups by advanced diagnostic tools, strongly support the recommend G6PD testing by the National Malaria Control Program and the subsequent safe treatment of P. vivax by primaquine for radical cure. Establishing a field monitoring system to achieve timely malaria elimination is mandatory to observe the safety of patients after PQ treatment.

Efficacy and Safety of Pyronaridine-Artesunate for the Treatment of Uncomplicated Plasmodium falciparum and Plasmodium vivax Malaria in Myanmar.

Four single-arm, prospective, clinical studies of pyronaridine-artesunate efficacy in uncomplicated Plasmodium falciparum or Plasmodium vivax malaria were conducted in Myanmar between 2017 and 2019. Eligible subjects were aged at least 6 years, with microscopically confirmed P. falciparum (n = 196) or P. vivax mono-infection (n = 206). Patients received pyronaridine-artesunate once daily for 3 days with follow-up until day 42 for P. falciparum or day 28 for P. vivax. For the primary efficacy analysis, adequate clinical and parasitological response (ACPR) in the per-protocol population at day 42 for P. falciparum malaria was 100% (88/88; 95% CI: 95.9, 100) in northern Myanmar (Kachin State and northern Shan State), and 100% (101/101; 95% CI: 96.4, 100) in southern Myanmar (Tanintharyi Region and Kayin State). Plasmodium falciparum day-3 parasite clearance was observed for 96.9% (190/196) of patients. Mutations in the P. falciparum Kelch propeller domain (K13) were detected in 39.0% (69/177) of isolates: F446I (14.7% [26/177]), R561H (13.0% [23/177]), C580Y (10.2% [18/177]), and P574L (1.1% [2/177]). For P. vivax, the day-28 ACPR was 100% (104/104; 95% CI: 96.5, 100) in northern Myanmar and 100% (97/97; 95% CI: 96.3, 100) in southern Myanmar. Across both P. vivax studies, 100% (206/206) of patients had day-3 parasite clearance. There were no adverse events. Pyronaridine-artesunate had excellent efficacy in Myanmar against P. falciparum and P. vivax and was well tolerated. This study supports the inclusion of pyronaridine-artesunate in national malaria treatment guidelines for Myanmar.

Artemether-Lumefantrine and Dihydroartemisinin-Piperaquine Retain High Efficacy for Treatment of Uncomplicated Plasmodium falciparum Malaria in Myanmar.

The emergence of artemisinin-resistant Plasmodium falciparum in the Greater Mekong Subregion threatens both the efficacy of artemisinin-based combination therapy (ACT), the first-line treatment for malaria, and prospects for malaria elimination. Monitoring of ACT efficacy is essential for ensuring timely updates to elimination policies and treatment recommendations. In 2014-2015, we assessed the therapeutic efficacies of artemether-lumefantrine (AL) and dihydroartemisinin-piperaquine (DP) for the treatment of uncomplicated P. falciparum at three study sites in Rakhine, Shan, and Kachin states in Myanmar. Patients presenting with uncomplicated P. falciparum malaria were enrolled, treated, and followed up for 28 days for AL or 42 days for DP. Both AL and DP demonstrated good therapeutic efficacy at all three study sites. The 28-day cure rate for AL was > 96% across all study sites, and the 42-day cure rate for DP was 100%. Parasitemia on day 3 was detected in 0%, 3.3%, and 3.6% of participants treated with AL at the Rakhine, Shan, and Kachin sites, respectively. No participants treated with DP were parasitemic on day 3. No evidence of P. falciparum k13 mutations was found at the Rakhine study site. A high prevalence of k13 mutations associated with artemisinin resistance was observed at the Kachin and Shan state study sites. These results confirm that ACT efficacy has been resilient in therapeutic efficacy study (TES) sentinel sites in Myanmar, despite the presence at some sites of k13 mutations associated with resistance. Studies are ongoing to assess whether this resilience persists.

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.