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Abstract: Triatoma dimidiata is one of the main vectors of Chagas disease, and it has been shown to be a species complex. In the Yucatán peninsula, Mexico, vector populations are non-domiciliated, and the transmission of Trypanosoma cruzi thus critically relies on vector dispersal. This leads us to study the morphologic variations in T. dimidiata wings with respect to genetic factors (sex and genotype at the ITS-2 locus), geographic location, and T. cruzi-infection status. Females were found to have larger and more symmetrical wings than males. Wing shape was influenced by ITS-2 genotypes, although differences are unlikely sufficient to allow taxonomic discrimination of the sibling species. Hybrids were shown to have similar fluctuating asymmetries in wing size and shape as parental species, but the level of asymmetry in shape varied slightly between villages. The two later findings are consistent with a high level of gene flow between parental species, and the high dispersal potential of these non-domiciliated vectors. More surprisingly, individuals infected with T. cruzi were found to have larger wings than non-infected ones. This effect, which was consistently observed across sexes, genotypes and villages, is likely to be due to a direct impact of T. cruzi on insect development. Sex and infection status are thus likely to be key factors influencing vector dispersal with important impacts on disease transmission, since dispersal directly controls the domestic abundance of these vectors. These aspects should be investigated further to fully capture the ecology and evolution of Chagas disease transmission by non-domiciliated vectors. [Copyright &y& Elsevier]

• A clean dataset tests recycling participation variation with distance. • Participation rates of recycling vary with distance: small, negative, significant. • Frequency of (non-zero) participation does not vary with distance. • Results are inconsistent with cost/benefit models and widespread assumptions. • Results suggest recycling field should use non-static models incorporating phases. The distance of recycling bins from households is often considered important by practitioners, but published evidence for this uses only indirect and self-reported data. This study aims to provide such evidence by obtaining a clean test using measured distances in a walled community with 1200 households with the same building types, local governance, recycling and waste arrangements. The number of deposits each month of food waste for recycling at a designated site are logged via smart-cards allocated per household. The number of days per month that each household deposits showed a highly significant - but small - negative correlation with distance of the bin: fewer householders participate if further away, accounting for 3% of the variation. Surprisingly, there is no variation with distance among those who do participate: their recycling frequency does not vary. This second result is not consistent with the first in terms of cost/benefit concepts assumed by government planners, nor with the static theories of behaviour currently used in waste management research. We recommend that recycling practitioners note the smallness of the contribution of distance to recycling performance, and not overrate it. And we recommend that researchers make better use of non-static models (which model different stages towards behaviour change), which our second result appears to call for. [ABSTRACT FROM AUTHOR]

• Machine learning (Boosted Regression Trees) was used to predict case fatality ratios for Ebola virus disease. • The case fatality ratios for Ebola in the West Africa epidemic showed substantial spatiotemporal heterogeneity. • Analysis using geospatial techniques (kriging and semivariograms) revealed that unexplained variation in the case fatality ratio estimates showed spatial autocorrelation but no temporal autocorrelation. • In Ebola outbreaks, machine learning and geospatial analysis, coupled with key domain knowledge, could be used to inform the outbreak response. For the 2013–2016 Ebola epidemic in West Africa, the largest Ebola virus disease (EVD) epidemic to date, we aim to analyse the patient mix in detail to characterise key sources of spatiotemporal heterogeneity in the case fatality ratios (CFR). We applied a non-parametric Boosted Regression Trees (BRT) imputation approach for patients with missing survival outcomes and adjusted for model imperfection. Semivariogram analysis and kriging were used to investigate spatiotemporal heterogeneities. CFR estimates varied significantly between districts and over time over the course of the epidemic. BRT modelling accounted for most of the spatiotemporal variation and interactions in CFR, but moderate spatial autocorrelation remained for distances up to approximately 90 km. Combining district-level CFR estimates and kriged district-level residuals provided the best linear unbiased predicted map of CFR accounting for the both explained and unexplained spatial variation. Temporal autocorrelation was not observed in the district-level residuals from the BRT estimates. This study provides new insight into the epidemiology of the 2013–2016 West African Ebola epidemic with a view of informing future public health contingency planning, resource allocation and impact assessment. The analytical framework developed in this analysis, coupled with key domain knowledge, could be deployed in real time to support the response to ongoing and future outbreaks. [ABSTRACT FROM AUTHOR]

Novel data and analyses have had an important role in informing the public health response to the COVID-19 pandemic. Existing surveillance systems were scaled up, and in some instances new systems were developed to meet the challenges posed by the magnitude of the pandemic. We describe the routine and novel data that were used to address urgent public health questions during the pandemic, underscore the challenges in sustainability and equity in data generation, and highlight key lessons learnt for designing scalable data collection systems to support decision making during a public health crisis. As countries emerge from the acute phase of the pandemic, COVID-19 surveillance systems are being scaled down. However, SARS-CoV-2 resurgence remains a threat to global health security; therefore, a minimal cost-effective system needs to remain active that can be rapidly scaled up if necessary. We propose that a retrospective evaluation to identify the cost-benefit profile of the various data streams collected during the pandemic should be on the scientific research agenda. [ABSTRACT FROM AUTHOR]

Limited access to Chagas disease diagnosis and treatment is a major obstacle to reaching the 2020 World Health Organization milestones of delivering care to all infected and ill patients. Colombia has been identified as a health system in transition, reporting one of the highest levels of health insurance coverage in Latin America. We explore if and how this high level of coverage extends to those with Chagas disease, a traditionally marginalised population. Using a mixed methods approach, we calculate coverage for screening, diagnosis and treatment of Chagas. We then identify supply-side constraints both quantitatively and qualitatively. A review of official registries of tests and treatments for Chagas disease delivered between 2008 and 2014 is compared to estimates of infected people. Using the Flagship Framework, we explore barriers limiting access to care. Screening coverage is estimated at 1.2% of the population at risk. Aetiological treatment with either benznidazol or nifurtimox covered 0.3–0.4% of the infected population. Barriers to accessing screening, diagnosis and treatment are identified for each of the Flagship Framework's five dimensions of interest: financing, payment, regulation, organization and persuasion. The main challenges identified were: a lack of clarity in terms of financial responsibilities in a segmented health system, claims of limited resources for undertaking activities particularly in primary care, non-inclusion of confirmatory test(s) in the basic package of diagnosis and care, poor logistics in the distribution and supply chain of medicines, and lack of awareness of medical personnel. Very low screening coverage emerges as a key obstacle hindering access to care for Chagas disease. Findings suggest serious shortcomings in this health system for Chagas disease, despite the success of universal health insurance scale-up in Colombia. Whether these shortcomings exist in relation to other neglected tropical diseases needs investigating. We identify opportunities for improvement that can inform additional planned health reforms. [ABSTRACT FROM AUTHOR]