The Puerto Rico Department of Health (PRDOH) is one of the Cabinet-level agencies directly created by Article 4, Section 6 of the Constitution of Puerto Rico. It is headed by a Secretary of Health, appointed by the Governor of Puerto Rico and requiring the advice and consent of the Senate of Puerto Rico. The Secretary of Health is eighth in the line of gubernatorial succession.
Dengue remains a major public health challenge, particularly in endemic areas like Puerto Rico, where its economic burden is substantial. This study aimed to update the economic burden of dengue in Puerto Rico using recent data from patients, hospitals, and insurance companies, providing a clearer picture of the current situation. We estimated the total number of dengue cases with fever who sought care by adjusting for underreporting through a robust statistical framework linking island-wide passive surveillance data to sentinel acute febrile illness surveillance. We obtained cost data from hospitals and conducted interviews with a random sample of people diagnosed with dengue (n = 101) from December 2021–November 2022, collecting detailed information on direct medical costs, non-medical costs, and indirect costs. We analyzed median, epidemic and long-term dengue incidence patterns from 2010–2023. We conducted a cost-of-illness analysis using Bayesian multiplier methods to adjust for underreporting, followed by a bottom-up costing approach during a typical median incidence year and an epidemic year to illustrate the current economic burden of dengue in Puerto Rico. In the median incidence year (2014), from 597 reported dengue cases we estimated 4500 [95
Real-time nowcasting enhances situational awareness by mitigating reporting delays that obscure transmission dynamics. We applied Nowcasting by Bayesian Smoothing (NobBS) to the 2024 dengue outbreak in Puerto Rico (PR), using case surveillance data from the PR Department of Health. The method accurately captured the epidemic trajectory and consistently outperformed a baseline model, although reporting anomalies occasionally reduced performance. We also conducted analyses by dengue virus serotype and health region, as well as previous years. For analyses with few dengue cases, a model in which parameters are jointly estimated across groups generally achieved better performance than the independent one. Historical analyses revealed that years with higher variability in reporting delays generally exhibited higher uncertainty. The findings here underscore key lessons for real-time dengue nowcasting: alternative models may be needed in complex circumstances, but with stable reporting patterns and continuous evaluation, nowcasts can be a reliable and valuable public health tool. ### Competing Interest Statement The authors have declared no competing interest. ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: The data used in the study is individual data that has been de-identified before using. I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes Simulated data and code to run the nowcasts and perform model validation are available on GitHub (https://github.com/CDCgov/PR\_nowcast\_2024).
OBJECTIVES:Puerto Rico's 2024-2025 dengue epidemic highlighted the need to understand how complementary surveillance systems capture cases and severity. We compared the Sentinel Enhanced Dengue Surveillance System (SEDSS) and the Passive Arboviral Disease Surveillance System (PADSS) in capturing characteristics of dengue cases during this epidemic and assessed their complementary roles in epidemic monitoring and public health preparedness. METHODS:We analyzed laboratory-confirmed dengue cases reported in SEDSS and PADSS from January 1, 2024, through January 31, 2025. SEDSS recruits at sentinel sites, collecting clinical, epidemiological, and laboratory data, while PADSS relies on clinician-initiated reporting across the island. We used descriptive statistics, cross-correlation analyses, and generalized additive models to compare temporal trends, demographic characteristics, clinical features, and severe dengue outcomes. RESULTS:SEDSS enrolled 373 dengue patients (7.0% of tested patients), while PADSS reported 6488 dengue patients (60.1% of tested patients). Both systems showed aligned epidemic peaks, although PADSS detected more cases overall. Compared with PADSS patients, SEDSS patients were younger (median age = 22 vs 27 y) and had higher proportions of warning signs, including mucosal bleeding (21.7% vs 6.9%), hemoconcentration (4.4% vs 0.1%), and restlessness (31.1% vs 7.5%) (P < .001 for all). Severe dengue was more common in SEDSS patients (9.1% vs 5.6%; P = .02), likely due to more detailed clinical data, with the highest rates among patients aged 10 to 19 years (16.3%) and <10 years (10.5%). SEDSS captured severe plasma leakage (6.2%), which was not recorded in PADSS. PADSS provided broader geographic coverage. CONCLUSIONS:SEDSS captures detailed clinical data, whereas PADSS provides broader coverage and higher case counts. Integrating both systems strengthens epidemic response, resource allocation, and public health decision-making.
The representativeness and timeliness of sentinel surveillance for endemic and emerging arboviral and respiratory diseases in low-resource settings are understudied. We compared laboratory-confirmed epidemic dengue, non-epidemic dengue, Zika, chikungunya, and COVID-19 (pre-Omicron and Omicron periods) cases reported in Puerto Rico's Sentinel Enhanced Dengue Surveillance System (SEDSS) with island-wide trends reported by the Department of Health's passive disease surveillance system (PADSS). We plotted trends over time to assess representativeness and used lagged cross-correlations to determine whether SEDSS reporting preceded PADSS. SEDSS trends were representative of island-wide trends for all pathogens. SEDSS preceded reporting in PADSS by up to three, eight, and two weeks for epidemic dengue, Zika, and pre-Omicron COVID-19, respectively. Increasing case trends for chikungunya occurred at broadly similar times in both systems, while temporal concordance was lower for non-epidemic dengue. In Puerto Rico, sentinel surveillance was representative of island-wide trends and could provide early warning for dengue epidemics and emerging diseases, such as Zika and COVID-19.
