Spatial Video and EpiExplorer: A Field Strategy to Contextualize Enteric Disease Risk in Slum Environments.

Disease risk associated with contaminated water, poor sanitation, and hygiene in informal settlement environments is conceptually well understood. From an analytical perspective, collecting data at a suitably fine scale spatial and temporal granularity is challenging. Novel mobile methodologies, such as spatial video (SV), can complement more traditional epidemiological field work to address this gap. However, this work then poses additional challenges in terms of analytical visualizations that can be used to both understand sub-neighborhood patterns of risk, and even provide an early warning system. In this paper, we use bespoke spatial programming to create a framework for flexible, fine-scale exploratory investigations of simultaneously-collected water quality and environmental surveys in three different informal settlements of Port-au-Prince, Haiti. We dynamically mine these spatio-temporal epidemiological and environmental data to provide insights not easily achievable using more traditional spatial software, such as Geographic Information System (GIS). The results include sub-neighborhood maps of localized risk that vary monthly. Most interestingly, some of these epidemiological variations might have previously been erroneously explained because of proximate environmental factors and/or meteorological conditions.

Development of a Monoclonal Antibody to a Vibriophage as a Proxy for Vibrio cholerae Detection.

Cholera is an acute watery, diarrheal disease that causes high rates of morbidity and mortality without treatment. Early detection of the etiologic agent of toxigenic Vibrio cholerae is important to mobilize treatment and mitigate outbreaks. Monoclonal antibody (mAb) based rapid diagnostic tests (RDTs) enable early detection in settings without laboratory capacity. However, the odds of an RDT testing positive are reduced by nearly 90% when the common virulent bacteriophage ICP1 is present. We hypothesize that adding a mAb for the common, and specific, virulent bacteriophage ICP1 as a proxy for V. cholerae to an RDT will increase diagnostic sensitivity when virulent ICP1 phage is present. In this study, we used an in-silico approach to identify immunogenic ICP1 protein targets that were conserved across disparate time periods and locations. Specificity of targets to cholera patients with known ICP1 was determined, and specific targets were used to produce mAbs in a murine model. Candidate mAbs to the head protein demonstrated specificity to ICP1 by Enzyme linked immunosorbent assay (ELISA) and an ICP1 phage neutralization assay. The limit of detection of the final mAb candidate for ICP1 phage particles spiked into cholera stool matrix was 8 × 105 PFU by Western blotting analysis. This mAb will be incorporated into a RDT prototype for evaluation in a future diagnostic study to test the guiding hypothesis behind this study.

Exploring convolutional neural networks and spatial video for on-the-ground mapping in informal settlements.

BACKGROUND: The health burden in developing world informal settlements often coincides with a lack of spatial data that could be used to guide intervention strategies. Spatial video (SV) has proven to be a useful tool to collect environmental and social data at a granular scale, though the effort required to turn these spatially encoded video frames into maps limits sustainability and scalability. In this paper we explore the use of convolution neural networks (CNN) to solve this problem by automatically identifying disease related environmental risks in a series of SV collected from Haiti. Our objective is to determine the potential of machine learning in health risk mapping for these environments by assessing the challenges faced in adequately training the required classification models. RESULTS: We show that SV can be a suitable source for automatically identifying and extracting health risk features using machine learning. While well-defined objects such as drains, buckets, tires and animals can be efficiently classified, more amorphous masses such as trash or standing water are difficult to classify. Our results further show that variations in the number of image frames selected, the image resolution, and combinations of these can be used to improve the overall model performance. CONCLUSION: Machine learning in combination with spatial video can be used to automatically identify environmental risks associated with common health problems in informal settlements, though there are likely to be variations in the type of data needed for training based on location. Success based on the risk type being identified are also likely to vary geographically. However, we are confident in identifying a series of best practices for data collection, model training and performance in these settings. We also discuss the next step of testing these findings in other environments, and how adding in the simultaneously collected geographic data could be used to create an automatic health risk mapping tool.

Draft Genome Sequence of an Environmental Vibrio cholerae Strain, 2012Env-25, Obtained Using Nanopore Sequencing Technology.

Vibrio cholerae is a halophilic Gram-negative bacterial species and the etiological agent of cholera. Here, we report the draft genome sequence of an environmental V. cholerae strain, 2012Env-25, obtained using Oxford Nanopore Technologies (ONT) to provide insights into the ecology, evolution, and pathogenic potential of this bacterium.

Acute Respiratory Illness in Rural Haiti.

OBJECTIVES: Acute Respiratory Infection (ARI) is the most common cause of childhood morbidity and mortality in developing countries, including Haiti. Our objective was to detect pathogens found in children with ARI in rural Haiti to help develop evidence-based guidelines for treatment and prevention. METHODS: Retrospective study of students with ARI at four schools in rural Haiti. Viral and/or bacterial pathogens were identified by qPCR in 177 nasal swabs collected from April 2013 through November 2015. RESULTS: Most common viruses detected were Rhinovirus (36%), Influenza A (16%) and Adenovirus (7%), and bacteria were Streptococcus pneumoniae (58%) and Staphylococcus aureus (28%). Compared to older children, children aged 3-5 years had more Influenza A (28% vs. 9%, p=0.002) and Adenovirus detected (14% vs. 3%, p=0.01). Similarly, S. pneumoniae was greatest in children 3-5 years old (71% 3-5yrs; 58% 6-15 years; 25% 16-20 years; p=0.008). Children 3-10 years old presented with fever more than children 11-20 years old (22% vs 7%; p=0.02) and were more often diagnosed with pneumonia (28% vs 4%, p<0.001). CONCLUSIONS: Younger children had increased fever, pneumonia, and detection of Influenza A and S. pneumoniae. These data support the need for influenza and pneumococcus vaccination in early childhood in Haiti.

Genetic Studies of Vibrio cholerae in South West Cameroon-A Phylogenetic Analysis of Isolates from the 2010-2011 Epidemic.

INTRODUCTION: During the cholera outbreak from 2010 to 2011 in Cameroon, 33,192 cases with 1,440 deaths (case fatality ratio 4.34%) were reported to the World Health Organization. Of these, the South West Region reported 3,120 clinical cases. This region is in the Equatorial Monsoon climatic subzone of Cameroon, close to the coast, raising questions as to whether cases were linked with development of environmental reservoirs. METHODS: In an investigation conducted by the Laboratory for Emerging Infectious Diseases, University of Buea, toxigenic V. cholerae O1 were isolated from diarrheal stool samples from 18 patients, with ages ranging from <3 to 70 years. Coordinates for clinical centers at which cases were identified were obtained using a handheld GPS, and were mapped using ArcGIS. Antibiotic susceptibility testing was performed using the Kirby 'Bauer agar disc diffusion method. The full genomes of these strains were sequenced with the Illumina MiSeq platform. De novo assembly of cholera genomes and multiple sequence alignment were carried out using the bioinformatics pipeline developed in the Emerging Pathogens Institute laboratory at the University of Florida. RESULTS/DISCUSSION: Genetic comparisons showed that isolates were closely related, with pairwise p-distances ranging from 2.25 to 14.52 10-5 nt substitutions per site, and no statistically significant correlation between the pairwise genetic distances and the geographic distances among sampling locations. Indeed, the phylogeny of the Cameroonian strains displays the typical star-like topology and intermixing of strains from different locations that are characteristic of an exponential outbreak localized around a relatively restricted area with occasional spillover to other parts of the country, likely mediated by direct human contact and human movement. Findings highlight the utility of whole genome sequencing and phylogenetic analysis in understanding transmission patterns at the local level.

Mapping to Support Fine Scale Epidemiological Cholera Investigations: A Case Study of Spatial Video in Haiti.

The cartographic challenge in many developing world environments suffering a high disease burden is a lack of granular environmental covariates suitable for modeling disease outcomes. As a result, epidemiological questions, such as how disease diffuses at intra urban scales are extremely difficult to answer. This paper presents a novel geospatial methodology, spatial video, which can be used to collect and map environmental covariates, while also supporting field epidemiology. An example of epidemic cholera in a coastal town of Haiti is used to illustrate the potential of this new method. Water risks from a 2012 spatial video collection are used to guide a 2014 survey, which concurrently included the collection of water samples, two of which resulted in positive lab results "of interest" (bacteriophage specific for clinical cholera strains) to the current cholera situation. By overlaying sample sites on 2012 water risk maps, a further fifteen proposed water sample locations are suggested. These resulted in a third spatial video survey and an additional "of interest" positive water sample. A potential spatial connection between the "of interest" water samples is suggested. The paper concludes with how spatial video can be an integral part of future fine-scale epidemiological investigations for different pathogens.

Diarrhea in young children from low-income countries leads to large-scale alterations in intestinal microbiota composition.

BACKGROUND: Diarrheal diseases continue to contribute significantly to morbidity and mortality in infants and young children in developing countries. There is an urgent need to better understand the contributions of novel, potentially uncultured, diarrheal pathogens to severe diarrheal disease, as well as distortions in normal gut microbiota composition that might facilitate severe disease. RESULTS: We use high throughput 16S rRNA gene sequencing to compare fecal microbiota composition in children under five years of age who have been diagnosed with moderate to severe diarrhea (MSD) with the microbiota from diarrhea-free controls. Our study includes 992 children from four low-income countries in West and East Africa, and Southeast Asia. Known pathogens, as well as bacteria currently not considered as important diarrhea-causing pathogens, are positively associated with MSD, and these include Escherichia/Shigella, and Granulicatella species, and Streptococcus mitis/pneumoniae groups. In both cases and controls, there tend to be distinct negative correlations between facultative anaerobic lineages and obligate anaerobic lineages. Overall genus-level microbiota composition exhibit a shift in controls from low to high levels of Prevotella and in MSD cases from high to low levels of Escherichia/Shigella in younger versus older children; however, there was significant variation among many genera by both site and age. CONCLUSIONS: Our findings expand the current understanding of microbiota-associated diarrhea pathogenicity in young children from developing countries. Our findings are necessarily based on correlative analyses and must be further validated through epidemiological and molecular techniques.

Survey of culture, goldengate assay, universal biosensor assay, and 16S rRNA Gene sequencing as alternative methods of bacterial pathogen detection.

Cultivation-based assays combined with PCR or enzyme-linked immunosorbent assay (ELISA)-based methods for finding virulence factors are standard methods for detecting bacterial pathogens in stools; however, with emerging molecular technologies, new methods have become available. The aim of this study was to compare four distinct detection technologies for the identification of pathogens in stools from children under 5 years of age in The Gambia, Mali, Kenya, and Bangladesh. The children were identified, using currently accepted clinical protocols, as either controls or cases with moderate to severe diarrhea. A total of 3,610 stool samples were tested by established clinical culture techniques: 3,179 DNA samples by the Universal Biosensor assay (Ibis Biosciences, Inc.), 1,466 DNA samples by the GoldenGate assay (Illumina), and 1,006 DNA samples by sequencing of 16S rRNA genes. Each method detected different proportions of samples testing positive for each of seven enteric pathogens, enteroaggregative Escherichia coli (EAEC), enterotoxigenic E. coli (ETEC), enteropathogenic E. coli (EPEC), Shigella spp., Campylobacter jejuni, Salmonella enterica, and Aeromonas spp. The comparisons among detection methods included the frequency of positive stool samples and kappa values for making pairwise comparisons. Overall, the standard culture methods detected Shigella spp., EPEC, ETEC, and EAEC in smaller proportions of the samples than either of the methods based on detection of the virulence genes from DNA in whole stools. The GoldenGate method revealed the greatest agreement with the other methods. The agreement among methods was higher in cases than in controls. The new molecular technologies have a high potential for highly sensitive identification of bacterial diarrheal pathogens.

Evaluation of ASSURE® Dengue IgA Rapid Test using dengue-positive and dengue-negative samples.

ASSURE® Dengue IgA Rapid Test, an immunochromatographic anti-Dengue IgA Rapid Test based on reverse flow technology, was evaluated using archived sera. The sera were obtained during hospital admission and discharge of 204 patients during 2000 to 2001 dengue outbreak in Bangladesh and 220 negative sera collected in 2009. Based on characterization by reference ELISA (nonstructural protein 1 [NS1] Ag ELISA, immunoglobulin M [IgM]-Cap ELISA, and immunoglobulin G [IgG]-Cap ELISA), 179 (87.7%) patients were positive for dengue infection, and the remaining 245 patients had nondengue febrile illness. The performance of Dengue IgA Rapid Test was compared to reference ELISA. Of 179 dengue-positive sera, 79 (44.1%) were positive by NS1 Ag ELISA, 174 (97.2%) were positive by IgM-Cap ELISA, and 142 (79.3%) were positive by IgG-Cap ELISA. Among 142 IgG-positive cases, 121 (85.2%) patients had shown high level of IgG (PanBio units ≥ 22, equivalent to hemagglutination inhibition (HI) titer ≥ 2560) during hospital admission, indicating secondary infections. Dengue IgA Rapid Test demonstrated 99.4% (178 of 179) sensitivity in diagnosing dengue infection with the ability to detect 100% primary (58 of 58) and 99.2% (120 of 121) secondary infections, and the specificity was found 99.2% (2 of 245). The capability of Dengue IgA Rapid Test in detecting dengue infection in terms of day of illness was comparable to reverse transcriptase polymerase chain reaction and was found better than in-house IgM ELISA. Compared with in-house IgM ELISA, Dengue IgA Rapid Test also detected similar number of dengue virus (DENV) 1, DENV 2, and more DENV 3 and DENV 4 cases. The overall performance thus suggested its usefulness as one of the dengue early diagnostic tools where diagnostic facility is limited.