Dengue virus (DV) non-cross-reactive Omicron wave COVID-19 serums enhanced DV3 infectivity in vitro.

Introduction. In India, the SARS-CoV-2 Delta wave (2020-2021) faded away with the advent of the Omicron variants (2021-present). Dengue incidences were observed to be less in Southeast Asia during the active years of the pandemic (2020-2021). However, dengue virus type 3 (DV3) cases were increasingly reported in this region (including India) concurrent with the progression of the Omicron waves since 2022.Hypothesis. What could be the reason(s) behind this unusual DV3 surge after an overall dip in dengue incidences in many parts of Southeast Asia?Aim. We, therefore, investigated the current state of cross-reactivity of prevalent (Omicron era) SARS-CoV-2 serums with different DV serotypes and evaluated the impact of such serums on DV neutralization in cell culture.Methodology. Fifty-five COVID-19 serum samples (January-September 2022) and three pre-pandemic archived serum samples from apparently healthy individuals were tested for DV or SARS-CoV-2 IgM/IgG using the lateral flow immunoassays. DV1-4 virus neutralization tests (VNTs) were done with the SARS-CoV-2 antibody (Ab)-positive serums in Huh7 cells. DV3 envelope (env) gene was PCR amplified and sequenced for three archived DV isolates, one from 2017 and two from 2021.Results. SARS-CoV-2 Ab-positive samples constituted 74.5 % of the serums. Of these, 41.5 % were DV cross-reactive and 58.5 % were not. The DV cross-reactive serums neutralized all DV serotypes (DV1-4), as per previous results and this study. The DV non-cross-reactive serums (58.5 %) also cross-neutralized DV1, 2 and 4 but increased DV3 infectivity by means of antibody-dependent enhancement of infection as evident from significantly higher DV3 titres in VNT compared to control serums. The DV3 envelope was identical among the three isolates, including isolate 1 used in VNTs. Our results suggest that DV cross-reactivity of SARS-CoV-2 serums diminished with the shift from Delta to Omicron prevalence. Such COVID-19 serums (DV non-cross-reactive) might have played a major role in causing DV3 surge during the Omicron waves.Conclusion. Patients suspected of dengue or COVID-19 should be subjected to virus/antigen tests and serological tests for both the diseases for definitive diagnosis, prognosis and disease management.

Risks of anxiety disorders, depressive disorders, and sleep disorders in patients with dengue fever: A nationwide, population-based cohort study.

BACKGROUND: Dengue virus (DENV) infection, a common mosquito-borne disease, has been linked to several mental disorders like depression and anxiety. However, the temporal risk of these disorders after DENV infection is not well studied. METHODS: This population-based cohort study encompassed 45,334 recently lab-confirmed dengue patients in Taiwan spanning 2002 to 2015, matched at a 1:5 ratio with non-dengue individuals based on age, gender, and residence (n = 226,670). Employing subdistribution hazard regression analysis, we assessed the immediate (<3 months), intermediate (3-12 months), and prolonged (>12 months) risks of anxiety disorders, depressive disorders, and sleep disorders post DENV infection. Corrections for multiple comparisons were carried out using the Benjamini-Hochberg procedure. RESULTS: A significant increase in depressive disorder risk across all timeframes post-infection was observed (<3 months [aSHR 1.90, 95% CI 1.20-2.99], 3-12 months [aSHR 1.68, 95% CI 1.32-2.14], and >12 months [aSHR 1.14, 95% CI 1.03-1.25]). Sleep disorder risk was higher only during 3-12 months (aSHR 1.55, 95% CI 1.18-2.04). No elevated anxiety disorder risk was found. Subgroup analysis of hospitalized dengue patients showed increased risk of anxiety disorders within 3 months (aSHR 2.14, 95% CI 1.19-3.85) and persistent risk of depressive disorders across all periods. Hospitalized dengue patients also had elevated sleep disorder risk within the first year. CONCLUSION: Dengue patients exhibited significantly elevated risks of depressive disorders in both the short and long term. However, dengue's impact on sleep disorders and anxiety seems to be short-lived. Further research is essential to elucidate the underlying mechanisms.

Atypical Dengue Outbreak in Odisha: Insights from the Entomological Investigations.

An outbreak of dengue fever struck Tikarapada village, Rayagada district (April 2020). Among 117 fever cases, 49 tested positive for the dengue NS1 antigen. To identify mosquito-related factors in the outbreak, a survey of 101 houses found Aedes breeding sites in 11.6% of containers. Aedes aegypti (79%) and Aedes albopictus (21%) emerged from collected pupae. The village exhibited high (house index = 24.8), (container index = 11.6), (pupal index = 32.7), and (Breteau index = 40.6) indices. The findings confirmed the presence of Aedes and ample breeding sites, suggesting their role in the outbreak. A report recommending integrated vector control measures was submitted to district and state health authorities.

Forecasting and mapping dengue fever epidemics in China: a spatiotemporal analysis.

BACKGROUND: Dengue fever (DF) has emerged as a significant public health concern in China. The spatiotemporal patterns and underlying influencing its spread, however, remain elusive. This study aims to identify the factors driving these variations and to assess the city-level risk of DF epidemics in China. METHODS: We analyzed the frequency, intensity, and distribution of DF cases in China from 2003 to 2022 and evaluated 11 natural and socioeconomic factors as potential drivers. Using the random forest (RF) model, we assessed the contributions of these factors to local DF epidemics and predicted the corresponding city-level risk. RESULTS: Between 2003 and 2022, there was a notable correlation between local and imported DF epidemics in case numbers (r = 0.41, P < 0.01) and affected cities (r = 0.79, P < 0.01). With the increase in the frequency and intensity of imported epidemics, local epidemics have become more severe. Their occurrence has increased from five to eight months per year, with case numbers spanning from 14 to 6641 per month. The spatial distribution of city-level DF epidemics aligns with the geographical divisions defined by the Huhuanyong Line (Hu Line) and Qin Mountain-Huai River Line (Q-H Line) and matched well with the city-level time windows for either mosquito vector activity (83.59%) or DF transmission (95.74%). The RF models achieved a high performance (AUC = 0.92) when considering the time windows. Importantly, they identified imported cases as the primary influencing factor, contributing significantly (24.82%) to local DF epidemics at the city level in the eastern region of the Hu Line (E-H region). Moreover, imported cases were found to have a linear promoting impact on local epidemics, while five climatic and six socioeconomic factors exhibited nonlinear effects (promoting or inhibiting) with varying inflection values. Additionally, this model demonstrated outstanding accuracy (hitting ratio = 95.56%) in predicting the city-level risks of local epidemics in China. CONCLUSIONS: China is experiencing an increasing occurrence of sporadic local DF epidemics driven by an unavoidably higher frequency and intensity of imported DF epidemics. This research offers valuable insights for health authorities to strengthen their intervention capabilities against this disease.

Exploring fine-scale urban landscapes using satellite data to predict the distribution of Aedes mosquito breeding sites.

BACKGROUND: The spread of mosquito-transmitted diseases such as dengue is a major public health issue worldwide. The Aedes aegypti mosquito, a primary vector for dengue, thrives in urban environments and breeds mainly in artificial or natural water containers. While the relationship between urban landscapes and potential breeding sites remains poorly understood, such a knowledge could help mitigate the risks associated with these diseases. This study aimed to analyze the relationships between urban landscape characteristics and potential breeding site abundance and type in cities of French Guiana (South America), and to evaluate the potential of such variables to be used in predictive models. METHODS: We use Multifactorial Analysis to explore the relationship between urban landscape characteristics derived from very high resolution satellite imagery, and potential breeding sites recorded from in-situ surveys. We then applied Random Forest models with different sets of urban variables to predict the number of potential breeding sites where entomological data are not available. RESULTS: Landscape analyses applied to satellite images showed that urban types can be clearly identified using texture indices. The Multiple Factor Analysis helped identify variables related to the distribution of potential breeding sites, such as buildings class area, landscape shape index, building number, and the first component of texture indices. Models predicting the number of potential breeding sites using the entire dataset provided an R² of 0.90, possibly influenced by overfitting, but allowing the prediction over all the study sites. Predictions of potential breeding sites varied highly depending on their type, with better results on breeding sites types commonly found in urban landscapes, such as containers of less than 200 L, large volumes and barrels. The study also outlined the limitation offered by the entomological data, whose sampling was not specifically designed for this study. Model outputs could be used as input to a mosquito dynamics model when no accurate field data are available. CONCLUSION: This study offers a first use of routinely collected data on potential breeding sites in a research study. It highlights the potential benefits of including satellite-based characterizations of the urban environment to improve vector control strategies.

Risk factors associated with dengue complications and death: A cohort study in Peru.

BACKGROUND: Dengue has emerged as an unprecedented epidemic in Peru, and it is anticipated that this issue will escalate further owing to climate change. This study aimed to determine the risk factors associated with death from dengue in patients treated at Hospital II in Pucallpa, Peru. METHODOLOGY: This retrospective cohort study collected information from the medical records of patients with a diagnosis of dengue treated at Hospital II Pucallpa-Peru between January 2019 and March 2023. The primary outcome was death, and the secondary outcome was death, development of severe dengue, or Intensive Care Unit (ICU) admission. Cox regression models were used to determine risk factors. FINDINGS: The clinical records of 152 patients were evaluated, with a median age of 27.5 years (interquartile range, 11-45). Among all patients, 29 (19.1%) developed severe dengue, 31 (20.4%) were admitted to the ICU, and 13 (8.6%) died during follow-up. In the survival analysis, bilirubin >1.2 mg/dL was associated with a higher risk of death aHR: 11.38 (95% CI: 1.2 106.8). Additionally, factors associated with poor prognosis included having 1 to 3 comorbidities aRR: 1.92 (1.2 to 3.2), AST ≥251 U/L aRR: 6.79 (2.2 to 21.4), history of previous dengue aRR: 1.84 (1.0 to 3.3), and fibrinogen ≥400 mg/dL aRR: 2.23 (1.2 to 4.1). SIGNIFICANCE: Elevated bilirubin was associated with death from dengue, whereas an increase in comorbidities and a history of previous dengue were related to a poor prognosis of the disease. Early identification of severe dengue would be more feasible with improved access to laboratory testing, particularly in tropical areas with a high dengue incidence.

An eco-epidemiological analysis of dengue outbreak in Port Blair, South Andaman Island, India.

BACKGROUND OBJECTIVES: In Port Blair, the capital of Andaman & Nicobar Islands, in the Bay of Bengal, India, there was a sudden increase in fever cases resembling the symptoms of dengue in the monsoon period of 2022. Hence, an investigation was carried out to find out epidemiological and entomological reasons behind the outbreak. METHODS: An entomological survey was carried out in 24 wards of Port Blair Municipal Council (PBMC) area, epidemiological data of last six years (January-December 2017-2021 and January-October 2022) and patient details of the year 2022 were collected. Both the epidemiological and entomological data were analyzed concerning time and place. RESULTS: During this outbreak period tyres (22.4%) came out as a major breeding habitat followed by small discarded materials (17.5%), metal drums (15.3%), and plastic drums (11.7%). In rainy season, peri-domestic breeding (55%) was more than the domestic breeding (45%) habitat. Ae. aegypti had a high preference for indoor large containers (100-1000 L) like plastic tank, metal drum and cement tank whereasAe. albopictus prefers to breed in medium sized plastic container (20-100 L) and outdoor water receptacles like tyres, flower pots, and domestic discarded materials. INTERPRETATION CONCLUSION: By source reduction, indoor space spray and outdoor fogging, vector density was controlled which curtailed the transmission and within eight weeks a decreasing trend of dengue cases was noticed. A regular entomological survey is crucial to know the seasonality and key breeding habitats of the vector for proper planning of vector control.

Endemic viral infections in immunocompromised hosts: Dengue, Chikungunya, Zika.

PURPOSE OF REVIEW: Arbovirus infections are a challenge for immunocompromised hosts who travel to or live in endemic regions or who receive organs or tissues from donors who travel or live in such areas. This review addresses Dengue (DENV), Chikungunya (CHIKV), and Zika (ZIKV) infections in hematological patients, hematopoietic cell or solid organ transplant recipients, and people with HIV (PWH). RECENT FINDINGS: Transmission is mainly due through Aedes mosquito bite. DENV and ZIKV may also be transmitted through blood, tissues or donor grafts. Clinical manifestations are quite similar and diagnosis requires laboratory confirmation to provide appropriate management. The best diagnostic method is PCR since serology may present false negative results in immunocompromised patients, or cross-reactivity as in the case of DENV and ZIKV. There is no specific treatment for any of these infections. SUMMARY: Educational and preventive measures are the best strategy: vector control, knowledge of the vector's habits, protection against mosquito bites, avoiding travel to endemic areas or with a current epidemic, and avoiding nonvector transmission according to local recommendations for donor deferral. Vaccination, currently only available for DENV, has not yet been studied in immunocompromised patients and is not currently recommended.

Assessing dengue risk globally using non-Markovian models.

Dengue is a vector-borne disease transmitted by Aedes mosquitoes. The worldwide spread of these mosquitoes and the increasing disease burden have emphasized the need for a spatio-temporal risk map capable of assessing dengue outbreak conditions and quantifying the outbreak risk. Given that the life cycle of Aedes mosquitoes is strongly influenced by habitat temperature, numerous studies have utilized temperature-dependent development rates of these mosquitoes to construct virus transmission and outbreak risk models. In this study, we contribute to existing research by developing a mechanistic model for the mosquito life cycle that accurately captures its non-Markovian nature. Beginning with integral equations to track the mosquito population across different life cycle stages, we demonstrate how to derive the corresponding differential equations using phase-type distributions. This approach can be further applied to similar non-Markovian processes that are currently described with less accurate Markovian models. By fitting the model to data on human dengue cases, we estimate several model parameters, allowing the development of a global spatiotemporal dengue risk map. This risk model employs temperature and precipitation data to assess the environmental suitability for dengue outbreaks in a given area.

The molecular epidemiology of a dengue virus outbreak in Taiwan: population wide versus infrapopulation mutation analysis.

Dengue virus (DENV) causes approximately 390 million dengue infections worldwide every year. There were 22,777 reported DENV infections in Tainan, Taiwan in 2015. In this study, we sequenced the C-prM-E genes from 45 DENV 2015 strains, and phylogenetic analysis based on C-prM-E genes revealed that all strains were classified as DENV serotype 2 Cosmopolitan genotype. Sequence analysis comparing different DENV-2 genotypes and Cosmopolitan DENV-2 sequences prior to 2015 showed a clade replacement event in the DENV-2 Cosmopolitan genotype. Additionally, a major substitution C-A314G (K73R) was found in the capsid region which may have contributed to the clade replacement event. Reverse genetics virus rgC-A314G (K73R) showed slower replication in BHK-21 and C6/36 cells compared to wildtype virus, as well as a decrease in NS1 production in BHK-21-infected cells. After a series of passaging, the C-A314G (K73R) mutation reverted to wildtype and was thus considered to be unstable. Next generation sequencing (NGS) of three sera collected from a single DENV2-infected patient at 1-, 2-, and 5-days post-admission was employed to examine the genetic diversity over-time and mutations that may work in conjunction with C-A314G (K73R). Results showed that the number of haplotypes decreased with time in the DENV-infected patient. On the fifth day after admission, two new haplotypes emerged, and a single non-synonymous NS4A-L115I mutation was identified. Therefore, we have identified a persistent mutation C-A314G (K73R) in all of the DENV-2 isolates, and during the course of an infection, a single new non-synonymous mutation in the NS4A region appears in the virus population within a single host. The C-A314G (K73R) thus may have played a role in the DENV-2 2015 outbreak while the NS4A-L115I may be advantageous during DENV infection within the host.

Seroprevalence of Arboviruses in a Malaria Hyperendemic Area in Southern Mali.

Diagnostics for febrile illnesses other than malaria are not readily available in rural sub-Saharan Africa. This study assessed exposure to three mosquito-borne arboviruses-dengue virus (DENV), Zika virus (ZIKV), and chikungunya virus (CHIKV)-in southern Mali. Seroprevalence for DENV, CHIKV, and ZIKV was analyzed by detection of IgG antibodies and determined to be 77.2%, 31.2%, and 25.8%, respectively. Among study participants, 11.3% were IgG-positive for all three arboviruses. DENV had the highest seroprevalence rate at all sites; the highest seroprevalence of CHIKV and ZIKV was observed in Bamba. The seroprevalence for all three arboviruses increased with age, and the highest seroprevalence was observed among adults older than 50 years. The prevalence of Plasmodium spp. in the cohort was analyzed by microscopy and determined to be 44.5% (N = 600) with Plasmodium falciparum representing 95.1% of all infections. This study demonstrates the co-circulation of arboviruses in a region hyperendemic for malaria and highlights the needs for arbovirus diagnostics in rural sub-Saharan Africa.

Dengue versus COVID-19: comparing the incidence of cardiovascular, neuropsychiatric and autoimmune complications.

BACKGROUND: While persistence of chronic symptoms following dengue infection has been documented in small prospective cohorts, population-based studies are limited. The post-acute risk of new-incident multi-systemic complications following dengue infection was contrasted against that following severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection in a multi-ethnic adult Asian population. METHODS: National testing and healthcare claims that databases in Singapore were utilized to build a retrospective population-based adult cohort with laboratory-confirmed infection during overlapping waves of SARS-CoV-2 and dengue transmission (1 July 2021 to 31 October 2022). Risks of new-incident cardiovascular/neuropsychiatric/autoimmune complications 31-300 days of post-dengue infection, contrasted with SARS-CoV-2 infection, were estimated using Cox regression with overlap weights. Risks were reported in terms of adjusted hazard ratio (aHR) and excess burden per 1000 persons. RESULTS: 11 707 dengue-infected individuals and 1 248 326 contemporaneous coronavirus disease 2019 (COVID-19) cases were included; the majority had mild initial infection not requiring hospitalization. Amongst dengue-infected individuals, there was 21% [aHR = 1.21 (1.06-1.38)] increased risk of any sequelae, with 55% [aHR = 1.55 (1.27-1.89)] increased risk of cardiovascular sequelae. Specifically, increased risk of dysrhythmias [aHR = 1.79(1.35-2.37)], ischemic heart disease [aHR = 1.45(1.12-1.89)], other cardiac disorders [aHR = 2.21(1.54-3.16)] and thrombotic disorders [aHR = 2.55(1.50-4.35)] was noted. Elevated risk of individual neuropsychiatric sequelae, including cerebrovascular disorders [aHR = 1.49(1.09-2.13)], cognition/memory disorders [aHR = 2.13(1.55-2.93)], extrapyramidal/movement disorders [aHR = 1.98(1.33-2.94)] and anxiety disorders [aHR = 1.61(1.01-2.56)], was observed in dengue-infected individuals compared to COVID-19 cases. Elevated risks of post-acute sequelae in dengue survivors were observed when contrasted against COVID-19 survivors infected during Delta/Omicron predominance, as well as across vaccination strata. CONCLUSION: Increased risk of post-acute cardiovascular/neuropsychiatric complications was observed in dengue survivors, when contrasted against COVID-19 survivors infected during Delta/Omicron predominance.

Geographically and Temporally Weighted Regression in Assessing Dengue Fever Spread Factors in YunnanBorder Regions.

Objective: This study employs the Geographically and Temporally Weighted Regression (GTWR) model to assess the impact of meteorological elements and imported cases on dengue fever outbreaks, emphasizing the spatial-temporal variability of these factors in border regions. Methods: We conducted a descriptive analysis of dengue fever's temporal-spatial distribution in Yunnan border areas. Utilizing annual data from 2013 to 2019, with each county in the Yunnan border serving as a spatial unit, we constructed a GTWR model to investigate the determinants of dengue fever and their spatio-temporal heterogeneity in this region. Results: The GTWR model, proving more effective than Ordinary Least Squares (OLS) analysis, identified significant spatial and temporal heterogeneity in factors influencing dengue fever's spread along the Yunnan border. Notably, the GTWR model revealed a substantial variation in the relationship between indigenous dengue fever incidence, meteorological variables, and imported cases across different counties. Conclusion: In the Yunnan border areas, local dengue incidence is affected by temperature, humidity, precipitation, wind speed, and imported cases, with these factors' influence exhibiting notable spatial and temporal variation.

Estimating dengue burden among family contacts through cluster investigation around probable cases in 2022 and 2023 in the Central Region, Burkina Faso.

BACKGROUND: In 2023, Burkina Faso experienced the largest dengue epidemic ever in Africa. This study aimed to estimate the prevalence of symptomatic, subclinical, and asymptomatic dengue and determine the associated factors among adult contacts of dengue in the Central Region, Burkina Faso. METHODS: This cross-sectional study included contacts of dengue probable cases through cluster sampling in 2022-2023. These suspected cases that tested positive were identified from the five health facilities (Pissy CMA, Saaba CM, Kossodo CMA, Samandin CM, and Marcoussis CSPS) that reported the highest number of cases in 2021 per district. All participants underwent dengue and malaria rapid diagnostic tests (RDT). Samples positive for non-structural 1 protein antigen (AgNS1) and/or immunoglobulin M (IgM) were tested for serotype detection by reverse transcription polymerase chain reaction (RT-PCR). Binary logistic regression was done to identify the determinants of asymptomatic, subclinical, and symptomatic dengue among contacts of probable dengue cases. RESULTS: A total of 484 contacts were included, mostly in 2023 (75.2%). Most participants were females (58.6%), residing (24.3%) and passing their daytime (23.1%) in Saaba. The overall prevalence of dengue was estimated at 15.1% [95% confidence interval (CI): 12.0-18.6%], representing cases not seeking care in hospitals. Asymptomatic cases represented 2.9% (95% CI: 1.6-4.8%). Subclinical and symptomatic cases accounted for 6.0% (95% CI: 4.1-8.5%) and 6.2% (95% CI: 4.2-8.7%), respectively. Of the 58 samples tested by RT-PCR, 10 were confirmed for serotype 3 in 2023. Malaria cases were estimated at 5.6% (95% CI: 3.7-8.0%). After adjustment, participants claiming that a virus transmits dengue were likelier to have asymptomatic dengue [adjusted odds ratio (aOR) = 7.1, 95% CI: 2.4-21.0]. From the multivariable analysis, subclinical dengue was statistically associated with being included in the study in 2023 (aOR = 30.2, 95% CI: 2.0-455.5) and spending the daytime at Arrondissement 4 (aOR = 11.5, 95% CI: 1.0-131.0). After adjustment, symptomatic dengue was associated with living less than 50 m away from cultivated land (aOR = 2.8, 95% CI: 1.1-6.9) and living less than 50 m from a stretch of water (aOR = 0.1, 95% CI: 0.0-0.6). CONCLUSIONS: The overall burden of dengue among populations not seeking care in hospitals was quite high, with few asymptomatic cases. Efforts to manage dengue cases should also target non-hospital cases and raise population awareness. The 2023 epidemic could be due to dengue virus (DENV)-3.

Serotype and genomic diversity of dengue virus during the 2023 outbreak in Pakistan reveals the circulation of genotype III of DENV-1 and cosmopolitan genotype of DENV-2.

Dengue, a mosquito-borne viral disease, poses a significant public health challenge in Pakistan, with a significant outbreak in 2023, prompting our investigation into the serotype and genomic diversity of the dengue virus (DENV). NS-1 positive blood samples from 153 patients were referred to the National Institute of Health, Pakistan, between July and October 2023. Among these, 98 (64.1%) tested positive using multiplex real-time PCR, with higher prevalence among males (65.8%) and individuals aged 31-40. Serotyping revealed DENV-1 as the predominant serotype (84.7%), followed by DENV-2 (15.3%). Whole-genome sequencing of 18 samples (DENV-1 = 17, DENV-2 = 01) showed that DENV-1 (genotype III) samples were closely related (>99%) to Pakistan outbreak samples (2022), and approx. > 98% with USA (2022), Singapore and China (2016), Bangladesh (2017), and Pakistan (2019). The DENV-2 sequence (cosmopolitan genotype; clade IVA) shared genetic similarity with Pakistan outbreak sequences (2022), approx. > 99% with China and Singapore (2018-2019) and showed divergence from Pakistan sequences (2008-2013). No coinfection with dengue serotypes or other viruses were observed. Comparisons with previous DENV-1 sequences highlighted genetic variations affecting viral replication efficiency (NS2B:K55R) and infectivity (E:M272T). These findings contribute to dengue epidemiology understanding and underscore the importance of ongoing genomic surveillance for future outbreak responses in Pakistan.

Microclimate factors related to dengue virus burden clusters in two endemic towns of Mexico.

In dengue-endemic areas, transmission control is limited by the difficulty of achieving sufficient coverage and sustainability of interventions. To maximize the effectiveness of interventions, areas with higher transmission could be identified and prioritized. The aim was to identify burden clusters of Dengue virus (DENV) infection and evaluate their association with microclimatic factors in two endemic towns from southern Mexico. Information from a prospective population cohort study (2·5 years of follow-up) was used, microclimatic variables were calculated from satellite information, and a cross-sectional design was conducted to evaluate the relationship between the outcome and microclimatic variables in the five surveys. Spatial clustering was observed in specific geographic areas at different periods. Both, land surface temperature (aPR 0·945; IC95% 0·895-0·996) and soil humidity (aPR 3·018; IC95% 1·013-8·994), were independently associated with DENV burden clusters. These findings can help health authorities design focused dengue surveillance and control activities in dengue endemic areas.

Is there an overestimation of dengue compared with that of other acute febrile syndromes in childhood?

A group of children with clinical suspicion of dengue were assessed to determine if there was an overestimation of dengue compared with that of leptospirosis and leishmaniasis. This descriptive and analytical cross-sectional study, based on the active search of participants with acute febrile illness, was conducted at two pediatric hospitals. The collection of clinical and epidemiological data was performed using questionnaires, and laboratory tests specific for dengue were performed using immunochromatographic, serological, and molecular methods. Dengue-negative samples were assessed for Leptospira and Leishmania spp. using molecular tests. Data were assessed using analysis of variance (ANOVA), the chi-square test, and Fisher's exact test. In total, 86 participants were evaluated, of whom 39 (45%) were positive for dengue fever, 4 (5%) for leptospirosis, and 1 (1%) for leishmaniasis. Forty-two participants (49%) presented dengue-like symptoms. The predominant age range for the virus was 3-10 years. Most clinical manifestations were nonspecific, with frequent concomitant gastrointestinal and respiratory symptoms. Furthermore, we found that the acute febrile syndrome in childhood persists as a challenge for health professionals, especially in the early days of the disease, due to a plurality of diagnostic hypotheses, associated with the difficulty of establishing well-defined symptoms in children, especially in infants. Dengue fever continues to be a frequent pathology with acute febrile infections in childhood; however, there is an overestimation of the disease, especially in endemic regions, when one considers only the clinical epidemiological diagnosis.

Space-time dispersion of dengue occurrence in epidemic and non-epidemic years in a municipality in the metropolitan region of Belo Horizonte, MG, 2011 to 2017.

OBJECTIVE: To analyze the transmission dynamics of dengue, a public health problem in Brazil and the Metropolitan Region of Belo Horizonte (MRBH). METHODS: The spatiotemporal evolution of the occurrence of dengue in the municipality of Contagem, state of Minas Gerais, a region with high arbovirus transmission, was analyzed. Furthermore, epidemic and non-epidemic periods were analyzed, based on probable cases of dengue. This is an ecological study that used the Notifiable Diseases Information System (SINAN) national database. The analyses were carried out considering the period from epidemiological week (EW) 40 of 2011 to 39 of 2017. Spatial analysis tools (crude and smoothed incidence rate, directional distribution ellipse, global Moran index and local Moran index, and spatial scanning time with definition of epidemiological risk) were used. RESULTS: The 2012 to 2013 and 2015 to 2016 epidemic cycles presented high incidence rates. The disease was concentrated in more urbanized areas, with a small increase in cases throughout the municipality. Seven statistically significant local clusters and areas with a high rate of cases and accentuated transmission in epidemic cycles were observed throughout the municipality. Spatial autocorrelation of the incidence rate was observed in all periods. CONCLUSION: The results of the present study highlight a significant and heterogeneous increase in dengue notifications in Contagem over the years, revealing distinct spatial patterns during epidemic and non-epidemic periods. Geoprocessing analysis identified high-risk areas, a piece of knowledge that can optimize the allocation of resources in the prevention and treatment of the disease for that municipality.

Dengue Burden and Factors Influencing Severity in Honduras: A Descriptive and Analytical Study.

BACKGROUND: Dengue is a disease that accounts for a major morbidity and mortality in Honduras. METHODS: This descriptive study used an analytical component based on the data from the National Virology Laboratory between 2016-2022. Ordinal logistic regression was used to identify the factors associated with the classification of dengue without warning signs (DWOS), dengue with warning signs (DWS), and severe dengue (SD). RESULTS: Overall, 14,687 dengue cases were included; 50.1% had DWOS, 36.5% had DWS, and 13.4% had SD. Patients that were more associated with a higher probability of DWS and SD were patients in the age groups 1-4 years (DWS OR 1.61; 95%CI:1.33-1.94), (SD OR 1.52; 95% CI:1.26-1.84), 5-9 years (DWS OR 2.01; 95% CI:1.68-2.40), (SD OR 2.00; 95% CI:1.67-2.40), and 10-19 years (DWS OR 1.55; 95% CI:1.30-1.85) (SD OR 1.57; 95% CI:1.31-1.88). The departments that were associated with a higher probability of DWS and SD were La Paz (OR 6.35; 95% CI:3.53-11.42), (OR 10.94; 95% CI:5.96-20.08), Copán (OR 6.94; 95% CI:5.05-9.53) (OR 7.33; 95% CI: 5.35-10.03), Valle (OR 5.22; 95% CI:1.25-21.82) (OR 10.71; 95% CI:2.21-51.88). CONCLUSIONS: During the study period, dengue presented endemic behavior, with peaks consistent with the last two epidemics in Honduras in 2015 and 2019. The main factors associated with dengue severity were age< 19 years, male sex, and being from La Paz, Copán, or Valle.