Trade, uneven development and people in motion: Used territories and the initial spread of COVID-19 in Mesoamerica and the Caribbean.

Mesoamerica and the Caribbean form a region comprised by middle- and low-income countries affected by the COVID-19 pandemic differently. Here, we ask whether the spread of COVID-19, measured using early epidemic growth rates (r), reproduction numbers (R t ), accumulated cases, and deaths, is influenced by how the 'used territories' across the regions have been differently shaped by uneven development, human movement and trade differences. Using an econometric approach, we found that trade openness increased cases and deaths, while the number of international cities connected at main airports increased r, cases and deaths. Similarly, increases in concentration of imports, a sign of uneven development, coincided with increases in early epidemic growth and deaths. These results suggest that countries whose used territory was defined by a less uneven development were less likely to show exacerbated COVID-19 patterns of transmission. Health outcomes were worst in more trade-dependent countries, even after controlling for the impact of transmission prevention and mitigation policies, highlighting how structural effects of economic integration in used territories were associated with the initial COVID-19 spread in Mesoamerica and the Caribbean.

Community-serving research addressing climate change impacts on vector-borne diseases.

The impacts of climate change on vector-borne diseases are uneven across human populations. This pattern reflects the effect of changing environments on the biology of transmission, which is also modulated by social and other inequities. These disparities are also linked to research outcomes that could be translated into tools for transmission reduction, but are not necessarily actionable in the communities where transmission occurs. The transmission of vector-borne diseases could be averted by developing research that is both hypothesis-driven and community-serving for populations affected by climate change, where local communities interact as equal partners with scientists, developing and implementing research projects with the aim of improving community health. In this Personal View, we share five principles that have guided our research practice to serve the needs of communities affected by vector-borne diseases.

Ensemble species distribution modeling of Culex tarsalis (Diptera: Culicidae) in the continental United States.

West Nile virus (WNV) is the primary mosquito-borne disease in the United States and has had case reports every year since its introduction in 1999. As such, it is critical that we characterize the distribution of WNV vectors. Estimates of Culex tarsalis Coquillett species distribution, a major WNV vector, are scarce. We used ensemble distribution modeling to estimate habitat suitability for this species across the contiguous United States by consolidating presence data from four publicly available mosquito trapping data servers. The central plains region and much of the western US were estimated to have high habitat suitability. We identified multiple metrics of temperature and precipitation to be important in predicting the occurrence of Cx. tarsalis in a given geographic area. Furthermore, we observed habitat suitability for Cx. tarsalis to be significantly higher in areas with a high incidence of West Nile neuroinvasive disease compared to areas with low WN disease incidence, suggesting that Cx. tarsalis is present in regions with a high incidence of disease.

Anopheles albimanus (Diptera: Culicidae) Ensemble Distribution Modeling: Applications for Malaria Elimination.

In the absence of entomological information, tools for predicting Anopheles spp. presence can help evaluate the entomological risk of malaria transmission. Here, we illustrate how species distribution models (SDM) could quantify potential dominant vector species presence in malaria elimination settings. We fitted a 250 m resolution ensemble SDM for Anopheles albimanus Wiedemann. The ensemble SDM included predictions based on seven different algorithms, 110 occurrence records and 70 model projections. SDM covariates included nine environmental variables that were selected based on their importance from an original set of 28 layers that included remotely and spatially interpolated locally measured variables for the land surface of Costa Rica. Goodness of fit for the ensemble SDM was very high, with a minimum AUC of 0.79. We used the resulting ensemble SDM to evaluate differences in habitat suitability (HS) between commercial plantations and surrounding landscapes, finding a higher HS in pineapple and oil palm plantations, suggestive of An. albimanus presence, than in surrounding landscapes. The ensemble SDM suggested a low HS for An. albimanus at the presumed epicenter of malaria transmission during 2018-2019 in Costa Rica, yet this vector was likely present at the two main towns also affected by the epidemic. Our results illustrate how ensemble SDMs in malaria elimination settings can provide information that could help to improve vector surveillance and control.

Computing with many spaces: Generalizing projections for the digital geohumanities and GIScience.

The digital geohumanities-and geographic computation generally-have advanced greatly by representing phenomena within geographic coordinate systems. More specifically, most visualizations and analyses only proceed once data are rendered into a single coordinate system via geolocation and one or more projections. But does it follow that geographic computation should require all phenomena to be represented in Euclidean or spherical geometry in a singular, absolute, Newtonian space? We suggest an approach to pluralizing the spaces available to geographic computation. We both supplement the technical architecture for projections and subtly reframe the purpose and meaning of projections. What we term numerical, generalized projections thereby become more central to GISystems. We suggest how existing libraries might be modified with minimal disruption (taking the widespread and foundational proj.4 library as example). We also envision modifications to existing OGC technical specifications for projections and coordinate systems. Finally, in conversation with the interpretative practice and nuanced spatialities of the digital geohumanities and critical geography, we further extend generalized projections to encompass spatial multiplicity, fragmented spaces, wormholes, and an expanded role for interruptions. This will facilitate: 1) interpretative approaches to scholarship and diverse constructions of space common in the humanities; 2) computational engagement with the ontological and epistemological commitments to relational space of critical human geography; and 3) scientific efforts to understand complex systems in the spaces and times that emerge from those systems' dynamics, revisiting a desire common in early quantitative geography; and 4) the desire for a broad basis of understanding geographic information in GIScience.