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BackgroundCutaneous and mucocutaneous leishmaniasis (CL/ML) cause significant morbidity globally and are vulnerable to changes from environmental events and conflict. In this ecological study, we aim to measure the associations between annual CL/ML cases, conflict intensity, and environmental factors between 2005 and 2022 globally. MethodsWe pulled annual case data from the WHO for 52 nations that had conflict intensity scores (ranging from 1–10) from the Bertelsmann Transformation Index. Using Earth observation tools, we gathered temperature, precipitation, vegetation, and humidity data, in addition to data on annual estimates of population, internal displacement, and GDP. We fit a negative binomial generalized additive model with a random nation-level intercept. ResultsConflict was positively associated with increased CL/ML across the studied nations (IRR: 1.09, 95% CI: 1.01–1.16, p = 0.02). Given this, intense conflict (a score of ten) was associated with over double the risk of CL/ML compared to the lowest conflict levels (score of one). We also identified a curvilinear relationship between mean temperature and cases, as well as between vegetation level and cases. Each had small pockets of significant increased and decreased risk, respectively. Larger mean humidity ranges were negatively associated with cases. Importantly, the relationship between conflict intensity and cases was mediated by displacement. DiscussionConflict is significantly associated with increased CL/ML cases. This is especially true at higher conflict levels, marking when conflict turns violent. The destruction of critical infrastructure (e.g., that related to healthcare, water, and sanitation) often seen during conflict could drive this association. Such environments can be hospitable to sandflies and can heighten individuals’ vulnerability through increased malnutrition, poverty, and displacement. Understanding this relationship is crucial for public health preparedness and response, especially as conflicts become increasingly violent and protracted. 

BackgroundThroughout the COVID-19 pandemic, US Centers for Disease Control and Prevention policies on face mask use fluctuated. Understanding how public health communications evolve around key policy decisions may inform future decisions on preventative measures by aiding the design of communication strategies (eg, wording, timing, and channel) that ensure rapid dissemination and maximize both widespread adoption and sustained adherence. ObjectiveWe aimed to assess how sentiment on masks evolved surrounding 2 changes to mask guidelines: (1) the recommendation for mask use on April 3, 2020, and (2) the relaxation of mask use on May 13, 2021. MethodsWe applied an interrupted time series method to US Twitter data surrounding each guideline change. Outcomes were changes in the (1) proportion of positive, negative, and neutral tweets and (2) number of words within a tweet tagged with a given emotion (eg, trust). Results were compared to COVID-19 Twitter data without mask keywords for the same period. ResultsThere were fewer neutral mask-related tweets in 2020 (β=–3.94 percentage points, 95% CI –4.68 to –3.21; P<.001) and 2021 (β=–8.74, 95% CI –9.31 to –8.17; P<.001). Following the April 3 recommendation (β=.51, 95% CI .43-.59; P<.001) and May 13 relaxation (β=3.43, 95% CI 1.61-5.26; P<.001), the percent of negative mask-related tweets increased. The quantity of trust-related terms decreased following the policy change on April 3 (β=–.004, 95% CI –.004 to –.003; P<.001) and May 13 (β=–.001, 95% CI –.002 to 0; P=.008). ConclusionsThe US Twitter population responded negatively and with less trust following guideline shifts related to masking, regardless of whether the guidelines recommended or relaxed mask usage. Federal agencies should ensure that changes in public health recommendations are communicated concisely and rapidly.