The patterns and driving forces of dengue invasions in China.

BACKGROUND: Global connectivity and environmental change pose continuous threats to dengue invasions from worldwide to China. However, the intrinsic relationship on introduction and outbreak risks of dengue driven by the landscape features are still unknown. This study aimed to map the patterns on source-sink relation of dengue cases and assess the driving forces for dengue invasions in China. METHODS: We identified the local and imported cases (2006-2020) and assembled the datasets on environmental conditions. The vector auto-regression model was applied to detect the cross-relations of source-sink patterns. We selected the major environmental drivers via the Boruta algorithm to assess the driving forces in dengue outbreak dynamics by applying generalized additive models. We reconstructed the internal connections among imported cases, local cases, and external environmental drivers using the structural equation modeling. RESULTS: From 2006 to 2020, 81,652 local dengue cases and 12,701 imported dengue cases in China were reported. The hotspots of dengue introductions and outbreaks were in southeast and southwest China, originating from South and Southeast Asia. Oversea-imported dengue cases, as the Granger-cause, were the initial driver of the dengue dynamic; the suitable local bio-socioecological environment is the fundamental factor for dengue epidemics. The Bio8 [odds ratio (OR) = 2.11, 95% confidence interval (CI): 1.67-2.68], Bio9 (OR = 291.62, 95% CI: 125.63-676.89), Bio15 (OR = 4.15, 95% CI: 3.30-5.24), normalized difference vegetation index in March (OR = 1.27, 95% CI: 1.06-1.51) and July (OR = 1.04, 95% CI: 1.00-1.07), and the imported cases are the major drivers of dengue local transmissions (OR = 4.79, 95% CI: 4.34-5.28). The intermediary effect of an index on population and economic development to local cases via the path of imported cases was detected in the dengue dynamic system. CONCLUSIONS: Dengue outbreaks in China are triggered by introductions of imported cases and boosted by landscape features and connectivity. Our research will contribute to developing nature-based solutions for dengue surveillance, mitigation, and control from a socio-ecological perspective based on invasion ecology theories to control and prevent future dengue invasion and localization.

C-reactive protein: An easy marker for early differentiation between leptospirosis and dengue fever in endemic area.

In tropical regions, leptospirosis and dengue fever (DF) are infectious diseases of epidemiological importance and have overlapping symptomatic features. The objective of this study was to identify the factors associated to diagnosing leptospirosis that differentiate it to DF at the initial hospital evaluation. A multicenter retrospective study was conducted comparing confirmed leptospirosis to DF cases. Clinical/laboratory findings were compiled at hospital admission on Reunion Island between 2018 and 2019. Multivariable logistic regression was used to identify the predictors of leptospirosis. In total, 98 leptospirosis and 673 DF patients were included with a mean age of 47.8 (±17.1) and 48.9 (±23.3) years, respectively. In the multivariate analyses, the main parameters associated with leptospirosis were: i) increased neutrophil counts, ii) C-reactive protein values, iii) the absence of prolonged partial thromboplastin time, and iv) a decrease of platelets. The most discriminating parameter was C-reactive protein (CRP). With a threshold of 50mg/L, CRP taken alone had a sensitivity of 94% and a specificity of 93.5%. The positive and negative likelihood ratios were 14.5 and 0.06, respectively. In the setting of an early presumptive diagnosis, we found that an increased CRP value (>50 mg/L) could help diagnose leptospirosis and aid the decision process for hospital surveillance and/or a potential antibiotic treatment regimen.

Genetic characterization of dengue virus serotype 1 circulating in Reunion Island, 2019-2021, and the Seychelles, 2015-2016.

BACKGROUND: An unprecedent increase in the number of cases and deaths reported from dengue virus (DENV) infection has occurred in the southwestern Indian ocean in recent years. From 2017 to mid-2021 more than 70,000 confirmed dengue cases were reported in Reunion Island, and 1967 cases were recorded in the Seychelles from 2015 to 2016. Both these outbreaks displayed similar trends, with the initial circulation of DENV-2 which was replaced by DENV-1. Here, we aim to determine the origin of the DENV-1 epidemic strains and to explore their genetic characteristics along the uninterrupted circulation, particularly in Reunion. METHODS: Nucleic acids were extracted from blood samples collected from dengue positive patients; DENV-1 was identified by RT-qPCR. Positive samples were used to infect VERO cells. Genome sequences were obtained from either blood samples or infected-cell supernatants through a combination of both Illumina or MinION technologies. RESULTS: Phylogenetic analyses of partial or whole genome sequences revealed that all DENV-1 sequences from Reunion formed a monophyletic cluster that belonged to genotype I and were closely related to one isolate from Sri Lanka (OL752439.1, 2020). Sequences from the Seychelles belonged to the same major phylogenetic branch of genotype V, but fell into two paraphyletic clusters, with greatest similarity for one cluster to 2016-2017 isolate from Bangladesh, Singapore and China, and for the other cluster to ancestral isolates from Singapore, dating back to 2012. Compared to publicly available DENV-1 genotype I sequences, fifteen non-synonymous mutations were identified in the Reunion strains, including one in the capsid and the others in nonstructural proteins (NS) (three in NS1, two in NS2B, one in NS3, one in NS4B, and seven in NS5). CONCLUSION: In contrast to what was seen in previous outbreaks, recent DENV-1 outbreaks in Reunion and the Seychelles were caused by distinct genotypes, all likely originating from Asia where dengue is (hyper)endemic in many countries. Epidemic DENV-1 strains from Reunion harbored specific non-synonymous mutations whose biological significance needs to be further investigated.

Social Media and the Influence of Fake News on Global Health Interventions: Implications for a Study on Dengue in Brazil.

Social media usage is growing globally, with an exponential increase in low- and middle-income countries. Social media changes the ways in which information-sharing occurs, intensifying the population's exposure to misinformation, including fake news. This has important repercussions for global health. The spread of fake news can undermine the implementation of evidence-based interventions and weaken the credibility of scientific expertise. This is particularly worrisome in countries, such as Brazil, in a sociopolitical context characterized by a lack of popular trust in public institutions. In this project report, we describe our experience with the spread of fake news through the social media platform WhatsApp during the implementation of a cluster randomized controlled trial aimed at reducing dengue incidence in children in Fortaleza (Brazil). During initial visits to selected clusters, the research team was met with resistance. Then, soon after data collection started, fake news began circulating about the study. As a result, the research team developed strategies to dispel suspicion and further promote the study. However, the climate of violence and mistrust, coupled with the COVID-19 pandemic, forced the interruption of the study in 2019. The lessons learned from our experience in Fortaleza can be useful to other researchers and practitioners implementing large-scale interventions in this era of health-related misinformation.

Dengue and COVID-19 co-infections: an important consideration in the tropics.

Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has affected >370 million individuals worldwide. Dengue is endemic in many countries and leads to epidemics at frequent intervals. In the tropics and subtropics, it is possible that individuals may be concurrently infected with both dengue and SARS-CoV-2. Differentiation between the two infections may be difficult from both a clinical and laboratory perspective. We have outlined the currently published findings (as of the end of December 2021) on patients with dengue and SARS-CoV-2 co-infections and have discussed the observed outcomes and management of such patients. Co-infections were more common in males >25 y of age, fever was not universal, 30-50% had medical comorbidities such as diabetes mellitus or hypertension and the case fatality rate was 16-28%.

World Dengue Day: A call for action.

Commemorating the 2021 ASEAN Dengue Day and advocacy for World Dengue Day, the International Society for Neglected Tropical Diseases (ISNTD) and Asian Dengue Voice and Action (ADVA) Group jointly hosted the ISNTD-ADVA World Dengue Day Forum-Cross Sector Synergies in June 2021. The forum aimed to achieve international and multisectoral coordination to consolidate global dengue control and prevention efforts, share best practices and resources, and improve global preparedness. The forum featured experts around the world who shared their insight, research experience, and strategies to tackle the growing threat of dengue. Over 2,000 healthcare care professionals, researchers, epidemiologists, and policy makers from 59 countries attended the forum, highlighting the urgency for integrated, multisectoral collaboration between health, environment, education, and policy to continue the march against dengue. Sustained vector control, environmental management, surveillance improved case management, continuous vaccine advocacy and research, capacity building, political commitment, and community engagement are crucial components of dengue control. A coordinated strategy based on science, transparency, timely and credible communication, and understanding of human behavior is needed to overcome vaccine hesitancy, a major health risk further magnified by the COVID-19 pandemic. The forum announced a strong call to action to establish World Dengue Day to improve global awareness, share best practices, and prioritize preparedness in the fight against dengue.

Changing epidemiology of dengue fever in children in South America.

PURPOSE OF REVIEW: Dengue is the most important arthropod-borne viral disease of public health significance. Its geographic distribution includes 128 countries worldwide, affecting 390 million people every year causing significant morbidity and mortality in children and adults everywhere. RECENT FINDINGS: In the past, severe dengue affected mostly adults in the Americas; this scenario has changed and now cases of dengue, severe dengue, and dengue deaths have increased in children under 15 years in Brazil and in Colombia. Dengue and COVID-19 co-infections have been reported in South America, with increased hospitalization. A dengue vaccine for 9-year-old children and older children and adults who have serological evidence of previous dengue has been licensed in many countries; a different dengue vaccine trial for 4-16-year-old children has demonstrated decrease in clinical dengue and decrease in dengue hospitalizations. SUMMARY: There is no specific treatment of dengue, and a changing climate, insecticide resistance and urban expansion have permitted the vector's spread, making the vector control almost impossible. The hope for dengue control relies on vaccine development; there is important research on this area with one vaccine already licensed and another one showing promising results.

Correlations between COVID-19 and dengue obtained via the study of South America, Africa and Southeast Asia during the 2020s.

A dramatic increase in the number of outbreaks of dengue has recently been reported, and climate change is likely to extend the geographical spread of the disease. In this context, this paper shows how a neural network approach can incorporate dengue and COVID-19 data as well as external factors (such as social behaviour or climate variables), to develop predictive models that could improve our knowledge and provide useful tools for health policy makers. Through the use of neural networks with different social and natural parameters, in this paper we define a Correlation Model through which we show that the number of cases of COVID-19 and dengue have very similar trends. We then illustrate the relevance of our model by extending it to a Long short-term memory model (LSTM) that incorporates both diseases, and using this to estimate dengue infections via COVID-19 data in countries that lack sufficient dengue data.

Assessing the efficacy of male Wolbachia-infected mosquito deployments to reduce dengue incidence in Singapore: study protocol for a cluster-randomized controlled trial.

BACKGROUND: Dengue is a severe environmental public health challenge in tropical and subtropical regions. In Singapore, decreasing seroprevalence and herd immunity due to successful vector control has paradoxically led to increased transmission potential of the dengue virus. We have previously demonstrated that incompatible insect technique coupled with sterile insect technique (IIT-SIT), which involves the release of X-ray-irradiated male Wolbachia-infected mosquitoes, reduced the Aedes aegypti population by 98% and dengue incidence by 88%. This novel vector control tool is expected to be able to complement current vector control to mitigate the increasing threat of dengue on a larger scale. We propose a multi-site protocol to study the efficacy of IIT-SIT at reducing dengue incidence. METHODS/DESIGN: The study is designed as a parallel, two-arm, non-blinded cluster-randomized (CR) controlled trial to be conducted in high-rise public housing estates in Singapore, an equatorial city-state. The aim is to determine whether large-scale deployment of male Wolbachia-infected Ae. aegypti mosquitoes can significantly reduce dengue incidence in intervention clusters. We will use the CR design, with the study area comprising 15 clusters with a total area of 10.9 km2, covering approximately 722,204 residents in 1713 apartment blocks. Eight clusters will be randomly selected to receive the intervention, while the other seven will serve as non-intervention clusters. Intervention efficacy will be estimated through two primary endpoints: (1) odds ratio of Wolbachia exposure distribution (i.e., probability of living in an intervention cluster) among laboratory-confirmed reported dengue cases compared to test-negative controls and (2) laboratory-confirmed reported dengue counts normalized by population size in intervention versus non-intervention clusters. DISCUSSION: This study will provide evidence from a multi-site, randomized controlled trial for the efficacy of IIT-SIT in reducing dengue incidence. The trial will provide valuable information to estimate intervention efficacy for this novel vector control approach and guide plans for integration into national vector control programs in dengue-endemic settings. TRIAL REGISTRATION: ClinicalTrials.gov, identifier: NCT05505682 . Registered on 16 August 2022. Retrospectively registered.

Overlap between dengue, Zika and chikungunya hotspots in the city of Rio de Janeiro.

BACKGROUND: Arboviruses represent a threat to global public health. In the Americas, the dengue fever is endemic. This situation worsens with the introduction of emerging, Zika fever and chikungunya fever, causing epidemics in several countries within the last decade. Hotspot analysis contributes to understanding the spatial and temporal dynamics in the context of co-circulation of these three arboviral diseases, which have the same vector: Aedes aegypti. OBJECTIVE: To analyze the spatial distribution and agreement between the hotspots of the historical series of reported dengue cases from 2000 to 2014 and the Zika, chikungunya and dengue cases hotspots from 2015 to 2019 in the city of Rio de Janeiro. METHODS: To identify hotspots, Gi* statistics were calculated for the annual incidence rates of reported cases of dengue, Zika, and chikungunya by neighborhood. Kendall's W statistic was used to analyze the agreement between diseases hotspots. RESULTS: There was no agreement between the hotspots of the dengue fever historical series (2000-2014) and those of the emerging Zika fever and chikungunya fever (2015-2019). However, there was agreement between hotspots of the three arboviral diseases between 2015 and 2019. CONCLUSION: The results of this study show the existence of persistent hotspots that need to be prioritized in public policies for the prevention and control of these diseases. The techniques used with data from epidemiological surveillance services can help in better understanding of the dynamics of these diseases wherever they circulate in the world.

COVID-19 Antibodies as Predictor of Severe Dengue among Hospitalized Children with Dengue Illness in the Post-third-wave Period of COVID-19 Infection in India.

BACKGROUND: There were widespread unconfirmed reports about the increased severity of dengue post-second wave of the COVID-19 pandemic in India. It is known that a second dengue infection with a different strain in an individual can trigger antibody-dependent enhancement (ADE). A similar phenomenon is hypothesized for severe COVID-19 infection since both dengue and COVID-19 are viral diseases with different and varying strains. However, much research is needed to confirm this hypothesis. In this context, we intended to assess the severity of dengue illness in relation to previous severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, possibly the role of COVID-19 antibodies as an early predictor of severe dengue illness. OBJECTIVE: To assess the utility of COVID-19 antibodies for early identification of severe dengue illness among children in the post-third-wave period of COVID-19 infection in India. MATERIALS AND METHODS: All hospitalized children with dengue illness were categorized as severe (shock and/or hemorrhage and/or multi-organ dysfunction) and non-severe dengue illness (dengue with or without warning signs) as per WHO definition. COVID-19 antibody titers were estimated in both groups. Clinical features and seroprevalence of COVID-19 antibodies were compared in both groups. RESULT: A total of 31 children were studied (13 severe and 18 non-severe dengue illnesses). The most common symptoms prior to presenting to the hospital included fever (100% in both groups), vomiting (85% in severe and 63% in non-severe), abdominal pain (85% in severe and 50% in non-severe), poor feeding (54% in severe and 28% in non-severe), and skin rashes (15% in severe and none in non-severe). The mean duration from the onset of fever to the first hospital visit was 4.6 days in severe illness and 5.3 days in non-severe dengue illness. The mean duration of hospitalization was 9.7 days in severe dengue illness and 4.1 days in non-severe dengue illness. While 92.3% of all severe dengue had significantly higher COVID-19 antibody titers, it was found elevated only in 44.4% of the children with non-severe dengue illness (p-value 0.0059; Yates' corrected p-value 0.0179). CONCLUSION: Clinical symptoms prior to presenting to the hospital were fever, vomiting, abdominal pain, poor oral feeding, and skin rashes. While fever, vomiting, and abdominal pain were seen commonly in both severe and non-severe dengue illnesses, the presence of skin rash during febrile phase is associated with severe dengue illness only. Hospitalized children having severe dengue had increased seroprevalence of COVID-19 antibodies (92.3%) compared to children with non-severe dengue (44.4%). However, there is no corelation of the severity of dengue illness with absolute values of COVID-19 antibody levels. Therefore, the presence of COVID-19 antibodies (previous COVID-19 infection) can be a predictor of severe illness in children with dengue especially if associated with poor oral feeding and skin rashes. The limitation of the study is its lesser sample size to conclude any definitive statement; nevertheless, the study paves way for a similar cohort of a larger sample size to draw conclusions.

Case report: A fatal outcome from co-infection of COVID-19 and dengue in the western region of Jeddah, Saudi Arabia.

Introduction: Co-infection of coronavirus disease 2019 (COVID-19) and dengue may coexist, as both viruses share similar laboratory and clinical features, making diagnosis and treatment challenging for health care professionals to prescribe, negatively impacting patient prognosis, and outcomes. Results and discussions: Both cases were positive for PCR and X-ray laboratory investigation at clinical examination, confirming COVID-19 and dengue co-infection, admission, and better management in referral hospitals are presented and discussed. The timeline provides detailed cases of situational analysis and the medical actions taken, as well as the outcomes. Conclusion: Both co-infection cases' (patients) health conditions had a poor prognosis and diagnosis and ended with undesired outcomes. Scaling up dual mosquito-vector linked viral diseases surveillance in understanding the transmission dynamics, early diagnosis, and the timely and safe monitoring of case management in clinical and hospital settings nationwide is paramount in curbing preventable co-infections and mortality.

Acute febrile illness among outpatients seeking health care in Bangladeshi hospitals prior to the COVID-19 pandemic.

Understanding the distribution of pathogens causing acute febrile illness (AFI) is important for clinical management of patients in resource-poor settings. We evaluated the proportion of AFI caused by specific pathogens among outpatients in Bangladesh. During May 2019-March 2020, physicians screened patients aged ≥2 years in outpatient departments of four tertiary level public hospitals. We randomly enrolled patients having measured fever (≥100.4°F) during assessment with onset within the past 14 days. Blood and urine samples were tested at icddr,b through rapid diagnostic tests, bacterial culture, and polymerase chain reaction (PCR). Acute and convalescent samples were sent to the Centers for Disease Control and Prevention (USA) for Rickettsia and Orientia (R/O) and Leptospira tests. Among 690 patients, 69 (10%) had enteric fever (Salmonella enterica serotype Typhi orSalmonella enterica serotype Paratyphi), 51 (7.4%) Escherichia coli, and 28 (4.1%) dengue detected. Of the 441 patients tested for R/O, 39 (8.8%) had rickettsioses. We found 7 (2%) Leptospira cases among the 403 AFI patients tested. Nine patients (1%) were hospitalized, and none died. The highest proportion of enteric fever (15%, 36/231) and rickettsioses (14%, 25/182) was in Rajshahi. Dhaka had the most dengue cases (68%, 19/28). R/O affected older children and young adults (IQR 8-23 years) and was detected more frequently in the 21-25 years age-group (17%, 12/70). R/O was more likely to be found in patients in Rajshahi region than in Sylhet (aOR 2.49, 95% CI 0.85-7.32) between July and December (aOR 2.01, 1.01-5.23), and who had a history of recent animal entry inside their house than not (aOR 2.0, 0.93-4.3). Gram-negative Enterobacteriaceae were the most common bacterial infections, and dengue was the most common viral infection among AFI patients in Bangladeshi hospitals, though there was geographic variability. These results can help guide empiric outpatient AFI management.

Geographical clusters of dengue outbreak in Singapore during the Covid-19 nationwide lockdown of 2020.

Dengue, a mosquito-transmitted viral disease, has posed a public health challenge to Singaporean residents over the years. In 2020, Singapore experienced an unprecedented dengue outbreak. We collected a dataset of geographical dengue clusters reported by the National Environment Agency (NEA) from 15 February to 9 July in 2020, covering the nationwide lockdown associated with Covid-19 during the period from 7 April to 1 June. NEA regularly updates the dengue clusters during which an infected person may be tagged to one cluster based on the most probable infection location (residential apartment or workplace address), which is further matched to fine-grained spatial units with an average coverage of about 1.35 km2. Such dengue cluster dataset helps not only reveal the dengue transmission patterns, but also reflect the effects of lockdown on dengue spreading dynamics. The resulting data records are released in simple formats for easy access to facilitate studies on dengue epidemics.