Dengue has historically been considered an urban disease associated with dense human populations and the built environment. Recently, studies suggest increasing dengue virus (DENV) transmission in rural populations. It is unclear whether these reports reflect recent spread into rural areas or ongoing transmission that was previously unnoticed, and what mechanisms are driving this rural transmission. We conducted a systematic review to synthesize research on dengue in rural areas and apply this knowledge to summarize aspects of rurality used in current epidemiological studies of DENV transmission given changing and mixed environments. We described how authors defined rurality and how they defined mechanisms for rural dengue transmission. We systematically searched PubMed, Web of Science, and Embase for articles evaluating dengue prevalence or cumulative incidence in rural areas. A total of 106 articles published between 1958 and 2021 met our inclusion criteria. Overall, 56% (n = 22) of the 48 estimates that compared urban and rural settings reported rural dengue incidence as being as high or higher than in urban locations. In some rural areas, the force of infection appears to be increasing over time, as measured by increasing seroprevalence in children and thus likely decreasing age of first infection, suggesting that rural dengue transmission may be a relatively recent phenomenon. Authors characterized rural locations by many different factors, including population density and size, environmental and land use characteristics, and by comparing their context to urban areas. Hypothesized mechanisms for rural dengue transmission included travel, population size, urban infrastructure, vector and environmental factors, among other mechanisms. Strengthening our understanding of the relationship between rurality and dengue will require a more nuanced definition of rurality from the perspective of DENV transmission. Future studies should focus on characterizing details of study locations based on their environmental features, exposure histories, and movement dynamics to identify characteristics that may influence dengue transmission.

BACKGROUND: Transmission models have a long history in the study of mosquito-borne disease dynamics. The mosquito biting rate (MBR) is an important parameter in these models, however, estimating its value empirically is complex. Modeling studies obtain biting rate values from various types of studies, each of them having its strengths and limitations. Thus, understanding these study designs and the factors that contribute to MBR estimates and their variability is an important step towards standardizing these estimates. We do this for an important arbovirus vector Aedes aegypti. METHODOLOGY/PRINCIPAL FINDINGS: We perform a systematic review using search terms such as biting rate and biting frequency combined with Aedes aegypti (Ae. aegypti or A. aegypti). We screened 3,201 articles from PubMed and ProQuest databases, of which 21 met our inclusion criteria. Two broader types of studies are identified: human landing catch (HLC) studies and multiple feeding studies. We analyze the biting rate data provided as well as the methodologies used in these studies to characterize the variability of these estimates across temporal, spatial, and environmental factors and to identify the strengths and limitations of existing methodologies. Based on these analyses, we present two approaches to estimate population mean per mosquito biting rate: one that combines studies estimating the number of bites taken per gonotrophic cycle and the gonotrophic cycle duration, and a second that uses data from histological studies. Based on one histological study dataset, we estimate biting rates of Ae. aegypti (0.41 and 0.35 bite/mosquito-day in Thailand and Puerto Rico, respectively). CONCLUSIONS/SIGNIFICANCE: Our review reinforces the importance of engaging with vector biology when using mosquito biting rate data in transmission modeling studies. For Ae. aegypti, this includes understanding the variation of the gonotrophic cycle duration and the number of bites per gonotrophic cycle, as well as recognizing the potential for spatial and temporal variability. To address these variabilities, we advocate for site-specific data and the development of a standardized approach to estimate the biting rate.

The relative importance of environmental pathways that results in enteropathogen transmission may vary by context. However, measurement of contact events between individuals and the environment remains a challenge, especially for infants and young children who may use their mouth and hands to explore their environment. Using a mixed-method approach, we combined 1) semistructured observations to characterize key behaviors associated with enteric pathogen exposure and 2) structured observations using Livetrak, a customized software application, to quantify the frequency and duration of contacts events among infants in rural Ecuador. After developing and iteratively piloting the structured observation instrument, we loaded the final list of prompts onto a LiveTrak pallet to assess environmental exposures of 6-month infants (N = 19) enrolled in a prospective cohort study of diarrheal disease. Here we provide a detailed account of the lessons learned. For example, in our field site, 1) most mothers reported washing their hands after diaper changes (14/18, 77.8%); however only a third (4/11, 36.4%) were observed washing their hands; 2) the observers noted that animal ownership differed from observed animal exposure because animals owned by neighboring households were reported during the observation; and 3) using Livetrak, we found that infants frequently mouthed their hands (median = 1.9 episodes/hour, median duration: 1.6 min) and mouthed surroundings objects (1.8 episodes/hour, 1.9 min). Structured observations that track events in real time, can complement environmental sampling, quantitative survey data and qualitative interviews. Customizing these observations enabled us to quantify enteric exposures most relevant to our rural Ecuadorian context.

Mosquito-borne diseases are a global burden; however, current methods of evaluating human-mosquito contact rates are expensive and time consuming. Validated surveys of self-reported mosquito bites may be an inexpensive way to determine mosquito presence and bite exposure level in an area, but this remains untested. In this study, a survey of self-reported mosquito bites was validated against household mosquito abundance from six communities in Esmeraldas, Ecuador. From February 2021 to July 2022, households were interviewed monthly, and five questions were used to ask participants how often they were bitten by mosquitoes at different times during the day. At the same time, adult mosquitoes were collected using a Prokopack aspirator. Species were identified and counted. Survey responses were compared with the total number of mosquitoes found in the home using negative binomial regression. More frequent self-reported mosquito bites were significantly associated with higher numbers of collected adult mosquitoes. These associations were driven by the prevalence of the dominant genera, Culex. These results suggest that surveys of perceived mosquito bites relate to actual mosquito presence, making them a potentially useful tool for determining the impact of vector-control interventions on community perceptions of risk but less useful for assessing the risk of nondominant species such as Aedes aegypti. Further work is needed to examine the robustness of these results in other contexts.

Dengue is recognized as a major health issue in large urban tropical cities but is also observed in rural areas. In these environments, physical characteristics of the landscape and sociodemographic factors may influence vector populations at small geographic scales, while prior immunity to the four dengue virus serotypes affects incidence. In 2019, a rural northwestern Ecuadorian community, only accessible by river, experienced a dengue outbreak. The village is 2-3 hours by boat away from the nearest population center and comprises both Afro-Ecuadorian and Indigenous Chachi households. We used multiple data streams to examine spatial risk factors associated with this outbreak, combining maps collected with an unmanned aerial vehicle (UAV), an entomological survey, a community census, and active surveillance of febrile cases. We mapped visible water containers seen in UAV images and calculated both the green-red vegetation index (GRVI) and household proximity to public spaces like schools and meeting areas. To identify risk factors for symptomatic dengue infection, we used mixed-effect logistic regression models to account for the clustering of symptomatic cases within households. We identified 55 dengue cases (9.5% of the population) from 37 households. Cases peaked in June and continued through October. Rural spatial organization helped to explain disease risk. Afro-Ecuadorian (versus Indigenous) households experience more symptomatic dengue (OR = 3.0, 95%CI: 1.3, 6.9). This association was explained by differences in vegetation (measured by GRVI) near the household (OR: 11.3 95% 0.38, 38.0) and proximity to the football field (OR: 13.9, 95% 4.0, 48.4). The integration of UAV mapping with other data streams adds to our understanding of these dynamics.

An accurate urine test for diverse populations with active tuberculosis could be transformative for preventing TB deaths. Urinary liporabinomannan (LAM) testing has been previously restricted to HIV co-infected TB patients. In this study we evaluate urinary LAM in HIV negative, pediatric and adult, pulmonary and extrapulmonary tuberculosis patients. We measured 430 microbiologically confirmed pretreatment tuberculosis patients and controls from Peru, Guinea Bissau, Venezuela, Uganda and the United States using three monoclonal antibodies, MoAb1, CS35, and A194, which recognize distinct LAM epitopes, a one-sided immunoassay, and blinded cohorts. We evaluated sources of assay variability and comorbidities (HIV and diabetes). All antibodies successfully discriminated TB positive from TB negative patients. ROAUC from the average of three antibodies' responses was 0.90; 95% CI 0.87-0.93, 90% sensitivity, 73.5% specificity (80 pg/mL). MoAb1, recognizing the 5-methylthio-D-xylofuranose(MTX)-mannose(Man) cap epitope, performed the best, was less influenced by glycosuria and identified culture positive pediatric (N = 19) and extrapulmonary (N = 24) patients with high accuracy (ROAUC 0.87, 95% CI 0.77-0.98, 0.90 sensitivity 0.80 specificity at 80 pg/mL; ROAUC = 0.96, 95% CI 0.92-0.99, 96% sensitivity, 80% specificity at 82 pg/mL, respectively). The MoAb1 antibody, recognizing the MTX-Man cap epitope, is a novel analyte for active TB detection in pediatric and extrapulmonary disease.