Dengue virus (DENV) is the most prevalent arbovirus in terms of human public health importance globally. In addition to DENV epidemiological surveillance, genomic surveillance may help investigators understand the epidemiological dynamics, geographic distribution, and temporal patterns of DENV circulation. Herein, we aimed to reconstruct the molecular epidemiology and phylogeny of DENV in Panama to connect the epidemiological history of DENV dispersal and circulation in Latin America. We retrospectively analyzed the epidemiological data obtained during 25 years of DENV surveillance in Panama. DENV was reintroduced in Panama in 1993 after a 35 year absence of autochthonous transmission. The increase in the number of total dengue cases has been accompanied by an increase in severe and fatal cases, with the highest case fatality rate recorded in 2011. All four serotypes were detected in Panama, which is characterized by serotype replacement and/or co-circulation of multiple serotypes. Phylogenetic analysis of datasets collected from envelope (E) gene sequences obtained from viruses isolated from human sera demonstrated that circulating viruses were highly diverse and clustered in distinct clades, with co-circulation of clades from the same genotype. Our analyses also suggest that Panamanian strains were related to viruses from different regions of the Americas, suggesting a continuous exchange of viruses within the Americas.

: Many people from poverty-stricken countries are migrating across South and Central America to reach the México–United States border, a movement exacerbated by the COVID-19 pandemic. Migrant people who begin their northbound journey in South America must transit across a significant geographic bottleneck, the Darién Gap, a mountainous rainforest region between Colombia and Panama. Most migrant people crossing this region originate from Cuba, Haiti, and Venezuela. Other people reach the shores of South American countries from west and central Africa or central and southeastern Asia and continue to the Darién Gap. Poverty and violence drive families with children to flee their homes and endure incalculable risks in their path. Children traveling with their families or as unaccompanied minors across the Darién Gap are exposed to life-threatening situations and human rights violations, including abuse, exploitation, malnourishment, and limited access to medical care. In addition to experiencing untreated medical illnesses, children experience mental health disorders during migration and after they reach their destination as a result of victimization and adverse traumatic experiences. Therefore, providing migrants, especially children, with rapid medical screenings and mental health support when they arrive at their destination is critical to reduce health inequities. Furthermore, making these interventions available during their transit and ensuring their safety may prevent further human rights abuses in children and families. Latin American governments must address the ongoing humanitarian crisis endured by migrants throughout their migratory path by offering access to essential healthcare services and safeguarding the rights and security of children and vulnerable groups.

The present analysis uses the data of confirmed incidence of dengue cases in the metropolitan region of Panama from 1999 to 2017 and climatic variables (air temperature, precipitation, and relative humidity) during the same period to determine if there exists a correlation between these variables. In addition, we compare the predictive performance of two regression models (SARIMA, SARIMAX) and a recurrent neural network model (RNN-LSTM) on the dengue incidence series. For this data from 1999–2014 was used for training and the three subsequent years of incidence 2015–2017 were used for prediction. The results show a correlation coefficient between the climatic variables and the incidence of dengue were low but statistical significant. The RMSE and MAPE obtained for the SARIMAX and RNN-LSTM models were 25.76, 108.44 and 26.16, 59.68, which suggest that any of these models can be used to predict new outbreaks. Although, it can be said that there is a limited role of climatic variables in the outputs the models. The value of this work is that it helps understand the behaviour of cases in a tropical setting as is the Metropolitan Region of Panama City, and provides the basis needed for a much needed early alert system for the region.

We report a case of reinfection by SARS-CoV-2 with the second virus harboring amino acid changes in the Spike protein (141-143del, D215A, ins215AGY, L452R, D614 G), orf1a, helicase, orf3a, and Nucleocapside. The virus associated with the reinfection, from an endemic lineage containing the S:L452R immune escape mutation, was circulating in Panama at the time.

Nowadays, the ability to make data-driven decisions in public health is of utmost importance. To achieve this, it is necessary for modelers to comprehend the impact of models on the future state of healthcare systems. Compartmental models are a valuable tool for making informed epidemiological decisions, and the proper parameterization of these models is crucial for analyzing epidemiological events. This work evaluated the use of compartmental models in conjunction with Particle Swarm Optimization (PSO) to determine optimal solutions and understand the dynamics of Dengue epidemics. The focus was on calculating and evaluating the rate of case reproduction, $R_0$, for the Republic of Panama. Three compartmental models were compared: Susceptible-Infected-Recovered (SIR), Susceptible-Exposed-Infected-Recovered (SEIR), and Susceptible-Infected-Recovered Human-Susceptible-Infected Vector (SIR Human-SI Vector, SIR-SI). The models were informed by demographic data and Dengue incidence in the Republic of Panama between 1999 and 2022, and the susceptible population was analyzed. The SIR, SEIR, and SIR-SI models successfully provided $R_0$ estimates ranging from 1.09 to 1.74. This study provides, to the best of our understanding, the first calculation of $R_0$ for Dengue outbreaks in the Republic of Panama.

Panama is a dengue endemic country which experienced a large outbreak in 2024 with over 32,000 reported cases and an incidence rate exceeding 700 cases per 100,000 inhabitants. Despite decades of circulation, the epidemiology of dengue and its heterogeneity in transmission intensity across Panama have not yet been characterised. We used 25 years of dengue case notification and population data from across Panama's 16 health regions and 82 districts to characterise dengue epidemiology and transmission intensity in the country. The analytic dataset comprised 128,890 dengue cases, of whom 52% were female and 48% were male; the mean age was 32.4 years (range 0–108 years). Ethnicity data are not collected in Panama's national dengue surveillance system and were therefore unavailable for this analysis. We characterised spatial heterogeneities in delay distributions by fitting parametric probability distributions to epidemiological delays, and demographic differences in the incidence risk ratio of dengue, and of dengue attributable hospitalisations and deaths. We also implemented catalytic models to infer the time-constant dengue force-of-infection (FOI) (i.e. the long-term average annual per capita risk of infection for a susceptible individual) from the age-stratified case notification data reported across Panama during 2000–2024 and explored age- and sex-related differences in dengue case reporting in sensitivity analyses. We observed spatial variation in delay distributions across health regions. The mean of the regional average time from symptoms onset to (i) reporting was 4.78 days (95% CI: 4.72–4.84 days), (ii) hospitalisation was 4.49 days (95% CI: 4.22–4.76), and (iii) recovery was 7.82 days (95% CI: 6.47–8.85 days). The dengue transmission intensity also showed spatial heterogeneity, with a mean regional per-serotype FOI of 0.008 (95% CrI: 0.004–0.015). The mean regional probability of detecting a secondary case was 0.415 (95% CrI: 0.233–0.871) and the probability of detecting a primary case relative to a secondary case was 0.131 (95% CrI: 0.049–0.348). We found evidence of age- and sex-related differences in dengue reporting. Given the estimated seroprevalence at nine years (obtained from the analysis of case-notification data) is below 40% across the whole country, dengue vaccination with TAK-003 is currently not recommended in Panama according to the WHO guidelines. In the future, age-stratified seroprevalence surveys would be useful to validate these estimates. This analysis provides a characterisation of dengue epidemiology and estimates of dengue FOI and infection burden in Panama across the last 25 years. This work will inform policy decisions at the Ministry of Health of Panama, providing guidance on resource allocation to strengthen the local surveillance system and to decision making on the potential implementation of new interventions. SENACYT-IFARHU (Panamá), 10.13039/501100000265 UK Medical Research Council and 10.13039/100010269 Wellcome Trust .