Despite an increase in dengue outbreaks and the arrival of chikungunya and Zika disease in Panama, studies on the demographic history of the invasive Aedes mosquitoes that are the principle vectors of these diseases are still lacking in this region. Here, we assess the genetic diversity of these mosquitoes in order to decipher their invasion histories into the Isthmus of Panama. DNA sequences from the mitochondrial cytochrome C oxidase I gene obtained from 30 localities in 10 provinces confirmed the presence of more than one mitochondrial haplogroup (i.e., maternal lineage) in each species. The invasion of Aedes albopictus was likely from temperate European countries, as the most frequent and widespread haplogroup in Panama harbored variants that are uncommon elsewhere in the Americas. Two infrequent and geographically restricted Ae. albopictus haplotypes appear to have subsequently invaded Panama from neighboring Costa Rica and the USA, respectively. In addition, we recovered two deeply divergent mitochondrial clades in Panamanian Aedes aegypti. The geographic origins of these clades is unknown, given that divergence in the mitochondrial genome is probably due to ancient population processes within the native range of Ae. aegypti, rather than due to its global expansion out of Africa. However, Panamanian Ae. aegypti mitochondrial sequences within the first clade were closely related to others from Colombia, Bolivia, Brazil, Mexico and the USA, suggesting two separate invasions from Western Hemisphere source populations. The pattern of increased genetic diversity in Aedes mosquitoes in Panama is likely facilitated by the numerous land and water inter-connections across the country, which allows them to enter via sea- and land-transportation from Europe, North, Central and South America. Our results here should be considered in disease mitigation programs if emergent arboviruses are to be effectively diminished in Panama through vector suppression.

Long term surveillance of vectors and arboviruses is an integral aspect of disease prevention and control systems in countries affected by increasing risk. Yet, little effort has been made to adjust space-time risk estimation by integrating disease case counts with vector surveillance data, which may result in inaccurate risk projection when several vector species are present, and when little is known about their likely role in local transmission. Here, we integrate 13 years of dengue case surveillance and associated Aedes occurrence data across 462 localities in 63 districts to estimate the risk of infection in the Republic of Panama. Our exploratory space-time modelling approach detected the presence of five clusters, which varied by duration, relative risk, and spatial extent after incorporating vector species as covariates. The Ae. aegypti model contained the highest number of districts with more dengue cases than would be expected given baseline population levels, followed by the model accounting for both Ae. aegypti and Ae. albopictus. This implies that arbovirus case surveillance coupled with entomological surveillance can affect cluster detection and risk estimation, potentially improving efforts to understand outbreak dynamics at national scales. Dengue cases have increased in tropical regions worldwide owing to urbanization, globalization, and climate change facilitating the spread of Aedes mosquito vectors. National surveillance programs monitor trends in dengue fever and inform the public about epidemiological scenarios where outbreak preventive actions are most needed. Yet, most estimations of dengue risk so far derive only from disease case data, ignoring Aedes occurrence as a key aspect of dengue transmission dynamic. Here we illustrate how incorporating vector presence and absence as a model covariate can considerably alter the characteristics of space-time cluster estimations of dengue cases.

The Republic of Panama has the second most unequally distributed wealth in Central America, has recently entered the list of countries affected by the COVID-19 pandemic, and has one of the largest testing rate per inhabitant in the region and consequently the highest incidence rate of COVID-19, making it an ideal location to discuss potential scenarios for assessing epidemic preparedness, and to outline research opportunities in the Region of the Americas. We address two timely important questions: What are the unique risks of COVID-19 in Panama that could help other countries in the Region be better prepared? And what kind of scientific knowledge can Panama contribute to the regional and global study of COVID-19? This paper provides suggestions about how the research community could support local health authorities plan for different scenarios and decrease public anxiety. It also presents basic scientific opportunities about emerging pandemic pathogens towards promoting global health from the perspective of a middle income country.

The first patient infected by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in Panama was reported on March 9, 2020. Here, we describe the first case of recovery from coronavirus disease 2019 (COVID-19) in the country. The patient was a 49-year-old male high school teacher, who did not show any primary symptoms of COVID-19 described by health authorities as the signs for medical attention. Nonetheless, he became severely ill over the course of 2 weeks and almost lost the battle against COVID-19. The identification of the first cluster of SARS-CoV-2 community transmission in the secondary school where the patient of this case report taught, led to the closure of the school and, a day after, the shutdown of the national education system, which may have prevented the spread and slowed the transmission rate of COVID-19 during the early stages of invasion. This case report highlights the need to increase awareness among healthcare professionals in Latin America to consider symptoms such as anosmia and dysgeusia as the sentinel signs of COVID-19 infection in order to prevent deaths, especially in high-risk patients.

We tested 700 serum samples collected throughout Panama from 2015 to 2016 for detecting antibodies and RNA of arboviruses. In convalescent specimens, microsphere immunoassay detected an antibody prevalence of 59.3% for dengue virus (DENV) and 30.3% for Zika virus (ZIKV), which included samples that were collected before the Panamanian surveillance system reported the first case of Zika in the country. For acute sera, the most common arbovirus was DENV with 18 positive samples (6%), followed by four (1.3%) of ZIKV and one (0.6%) of chikungunya virus (CHIKV). Our results indicate a change in the chronology of when ZIKV was first detected in Panama and stress the importance of integrating various approaches to enable improved surveillance of both endemic and emerging arboviruses.

Long term surveillance of vectors and arboviruses is an integral aspect of disease prevention and control systems in countries affected by increasing risk. Yet, little effort has been made to adjust space-time risk estimation by integrating disease case counts with vector surveillance data, which may result in inaccurate risk projection when several vector species are present, and little is known about their likely role in local transmission. Here, we integrate 13 years of dengue case surveillance and associatedAedesoccurrence data across 462 localities in 63 districts to estimate the risk of infection in the Republic of Panama. Our space-time modelling approach detected the presence of five clusters, which varied by duration, relative risk, and spatial extent after incorporating vector species as covariates. Dengue prevalence (n = 49,910) was predicted by the presence of residentAedes aegyptialone, while all other covariates exhibited insignificant statistical relationships with it, including the presence and absence of invasiveAedes albopictus. Furthermore, theAe. aegyptimodel contained the highest number of districts with more dengue cases than would be expected given baseline population levels. This implies that arbovirus case surveillance coupled with entomological surveillance can affect cluster detection and risk estimation, improving efforts to understand outbreak dynamics at national scales.Author Summary: Dengue cases have increased in tropical regions worldwide owing to climate change, urbanization, and globalization facilitating the spread ofAedesmosquito vectors. National surveillance programs monitor trends in dengue fever and inform the public about epidemiological scenarios where outbreak preventive actions are most needed. Yet, most estimations of dengue risk so far derive only from disease case data, ignoringAedesoccurrence as a key aspect of dengue transmission dynamic. Here we illustrate how incorporating vector presence and absence as a model covariate can considerably alter the characteristics of space-time cluster estimations of dengue cases. We further show thatAe. aegyptihas likely been a greater driver of dengue infection in high risk districts of Panama thanAe. albopictus, and provide a discussion of possible public health implications of both spatial and non-spatial model outcomes.