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.
SARS-COV-2 is the most recent from a series of emerging pathogens stressing national health systems. Initially restricted to Hubei province in China, COVID-19, the disease caused by SARS-COV-2 has become pandemic, reaching almost every nation on our planet. Here, we present an estimate of the Basic Reproduction Number (R0) for this disease based on confirmed cases recorded during the initial 30 days of transmission. Based on local transmission data for the six initial days of transmission, we estimated (mean ± SE) R0 = 2.58 ± 2.43. R0 was reduced by up to 56% to R0 = 1.12 ± 0.02 following suppression measures in place by April 4th, 2020. Independent estimates for the time-varying reproduction number (Rt) based on the serial interval distribution estimated for China showed that after 30 days, Rt decreased reaching a value of 0.914 ± 0.104 on April 4th, 2020. In this study, we also describe the suppression strategies in place in Costa Rica and compare their impacts with those implemented in Panamá and Uruguay, provided these three middle-income countries have similar demographic and economic indicators. However, these three countries have structurally different health systems and have resorted to different suppression measures against COVID-19. We compare the early epidemic growth curves in the three countries using an exponential deceleration model. We found the lowest epidemic growth rate in Costa Rica, followed by Panamá and then Uruguay, while the highest deceleration was observed in Uruguay, followed by Costa Rica and Panamá. We discuss how the unified, universal healthcare system of Costa Rica has been vital to successfully manage the early stage of the COVID-19 epidemic and call for the developments of precision public health tools to further improve epidemic health surveillance in Costa Rica.
Costa Rica is near malaria elimination. This achievement has followed shifts in malaria health policy. Here, we evaluate the impacts that different health policies have had on malaria transmission in Costa Rica from 1913 to 2018. We identified regime shifts and used regression models to measure the impact of different health policies on malaria transmission in Costa Rica using annual case records. We found that vector control and prophylactic treatments were associated with a 50% malaria case reduction in 1929–1931 compared with 1913–1928. DDT introduction in 1946 was associated with an increase in annual malaria case reduction from 7.6% (1942–1946) to 26.4% (1947–1952). The 2006 introduction of 7-day supervised chloroquine and primaquine treatments was the most effective health policy between 1957 and 2018, reducing annual malaria cases by 98% (2009–2018) when compared with 1957–1968. We also found that effective malaria reduction policies have been sensitive to natural catastrophes and extreme climatic events, both of which have increased malaria transmission in Costa Rica. Currently, outbreaks follow malaria importation into vulnerable areas of Costa Rica. This highlights the need to timely diagnose and treat malaria, while improving living standards, in the affected areas.
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