Dengue is the most common arboviral disease in the tropical and sub-tropical regions of the world. Like other regions, dengue-endemic areas have faced the additional public health and socio-economic impact of the ongoing coronavirus disease 2019 (COVID-19) pandemic. COVID-19 and dengue co-infections have been reported, with complicated patient management and care requirements. This review aimed to collate and synthesise current knowledge on the clinical features and outcomes of COVID-19 and dengue virus co-infection, a potentially important new dimension to be considered in public health management of the COVID-19 pandemic. A systematic literature review was conducted using PubMed, Web of Science and Scopus databases from 1st January to 21st November 2020. The key search terms used were “dengue” and “coronavirus”. Descriptive analysis with graphical illustrations were used to present the clinical and laboratory parameters of the co-infection. Thirteen published papers and four news articles were included in the review. Most studies were case reports with a detailed description of the clinical and laboratory characteristics of the co-infection. All cases were in adults with the exception of a six-year old child. The common symptoms of co-infection were fever, dyspnea, headache, and cough. Common laboratory results included thrombocytopenia, lymphocytopenia, elevated transaminases, and leukopenia. Serious outcomes of co-infection included septic shock, acute respiratory disease syndrome and multi-organ failure, leading to death in some patients. COVID-19 and dengue co-infection was associated with severe disease and fatal outcomes. The correct diagnosis and treatment of co-infection poses a substantial challenge due to the overlapping clinical and laboratory parameters. Therefore, confirmative diagnostic tests are necessary for accurate and timely diagnosis and patient management.

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Clinical features and outcomes of COVID-19 and dengue co-infection: a systematic review.

Objective Older people are the most vulnerable group for developing SARS-CoV-2 infection. Although vaccination against coronavirus disease 2019 (COVID-19) reduces infection, hospitalization, and mortality rates, some older people have refused to get vaccinated. Our study aimed to evaluate factors associated with COVID-19 vaccine hesitancy among Thai seniors. Methods We conducted a cross-sectional telephone survey on vaccine hesitancy in a geriatric clinic at Ramathibodi Hospital in Bangkok, Thailand. Patients aged ≥60 years were contacted and interviewed by trained interviewers between June 20 and July 25, 2021. Results In total, we interviewed 282 participants aged 60-93 years (mean age 73.0±7.5 years). We found that 44.3% of participants were hesitant to get a COVID-19 vaccination. Factors associated with high vaccine hesitancy were low education, lack of confidence in the healthcare system's ability to treat patients with COVID-19, vaccine manufacturers, being offered a vaccine from an unexpected manufacturer, and a low number of new COVID-19 cases per day. Conclusion The prevalence of COVID-19 vaccine hesitancy among Thai seniors is relatively high, and is associated with specific factors. These findings will help in promoting COVID-19 vaccination among Thailand's senior citizens.

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Factors associated with COVID-19 Vaccine Hesitancy in Thai Seniors.

SARS-CoV-2 seroprevalence and associated factors in Manaus, Brazil: baseline results from the DETECTCoV-19 cohort study.

Background: Twice city of Manaus located in the Brazilian rainforest, has experienced a health system collapse due to the SARS-CoV-2 pandemic However, little is known about which groups among the general population have been more affected In this report, we present the overall prevalence of SARS-CoV-2 infection and associated factors from the DETECTCoV-19 cohort 

Methods: A convenience sampling strategy via online advertising recruited 3046 adults Sociodemographic characteristics, COVID-19-related symptoms, COVID-19 testing, self-medication and prescribed medications were recorded Serum anti-SARS-CoV-2 nucleocapsid IgG antibodies were measured with an in-house ELISA Prevalence ratios (PR) were obtained using cluster-corrected and adjusted Poisson’s regression models 

Findings: A crude positivity rate among asymptomatic and symptomatic individuals, was estimated at 29·10%, with a maximum seroprevalence of 41·53% corrected by test characteristics and an antibody decay rate of 27% Regression models demonstrated a strong association towards marginalized low-income and vulnerable residents with limited health access Presence of a COVID-19 case (PR 1·39, 1·24-1·57) or death (PR 2·14, 1·74-2·62) in a household increased greatly the risk of other household members acquiring infection SARS-CoV-2 seroprevalence was higher among those who self-medicated to prevent infection (PR 1·36, 1·27-1·46)  

Interpretation: High SARS-CoV-2 seropositivity reveals a much burdensome scenario than estimations based on confirmed COVID-19 cases in Manaus  Overall, prevalence of SARS-CoV-2 antibody response demonstrated a disproportionate social and economic disparity among the study participants The syndemic nature of COVID-19 in the Amazon region needs differential policies and urgent solutions to control the pandemic  

Funding:  Research was funded by Ministry of Education (MEC), Brazil BBS, IVPF, ROS, ARCB and WBSS received scholarship from CAPES DSSS, TBNM, MFF and NOC received scholarship from FAPEAM

Declaration of Interests: The authors declare no conflict of interest

Ethics Approval Statement: The research ethics committee of Federal University of Amazonas (UFAM) approved this study (CAAE:34906920·4·0000·5020) in accordance with Brazilian law

SARS-CoV-2 Seroprevalence and Associated Factors in Manaus, Brazil: Baseline Results from the DETECTCoV-19 Cohort Study

A mathematical model for the co-interaction of COVID-19 and dengue transmission dynamics is formulated and analyzed. The sub-models are shown to be locally asymptotically stable when the respective reproduction numbers are below unity. Using available data sets, the model is fitted to the cumulative confirmed daily COVID-19 cases and deaths for Brazil (a country with high co-endemicity of both diseases) from February 1, 2021 to September 20, 2021. The fitting was done using the fmincon function in the Optimization Toolbox of MATLAB. Parameters denoting the COVID-19 contact rate, death rate and loss of infection acquired immunity to COVID-19 were estimated using the two data sets. The model is then extended to include optimal control strategies. The appropriate conditions for the existence of optimal control and the optimality system for the co-infection model are established using the Pontryagin's Principle. Different control strategies and their cost-effectiveness analyses were considered and simulated for the model, which include: controls against incident dengue and COVID-19 infections, control against co-infection with a second disease and treatment controls for both dengue and COVID-19. Highlights of the simulation results show that: (1) dengue prevention strategy could avert as much as 870,000 new COVID-19 infections; (2) dengue only control strategy or COVID-19 only control strategy significantly reduces new co-infection cases; (3) the strategy implementing control against incident dengue infection is the most cost-effective in controlling dengue and COVID-19 co-infections.

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COVID-19 and dengue co-infection in Brazil: optimal control and cost-effectiveness analysis.

Serological cross-reaction and coinfection of dengue and COVID-19 in Asia: Experience from Indonesia.

BACKGROUND
Biomarkers that are cost-effective and accurate for predicting severe coronavirus disease 2019 (COVID-19) are urgently needed. We would like to assess the role of various inflammatory biomarkers on admission as disease severity predictors and determine the optimal cut-off of the neutrophile-to-lymphocyte ratio (NLR) for predicting severe COVID-19.


METHODS
We conducted a cross-sectional study in six hospitals in Bali and recruited real-time PCR-confirmed COVID-19 patients aged >18 y from June to August 2020. Data collection included each patient's demographic, clinical, disease severity and hematological data. Multivariate and receiver operating characteristic curve analyses were performed.


RESULTS
A total of 95 Indonesian COVID-19 patients were included. The highest NLR among severe patients was 11.5±6.2, followed by the non-severe group at 3.3±2.8. The lowest NLR was found in the asymptomatic group (1.9±1.1). The CD4+ and CD8+ values were lowest in the critical and severe disease groups. The area under the curve of NLR was 0.959. Therefore, the optimal NLR cut-off value for predicting severe COVID-19 was ≥3.55, with sensitivity at 90.9% and a specificity of 16.7%.


CONCLUSIONS
Lower CD4+ and CD8+ and higher NLR values on admission are reliable predictors of severe COVID-19 among Indonesian people. NLR cut-off ≥3.55 is the optimal value for predicting severe COVID-19.

https://academic.oup.com/trstmh/advance-article-pdf/doi/10.1093/trstmh/trad012/49791389/trad012.pdf

Putu Dyah Widyaningsih

Papers

Serological cross-reaction and coinfection of dengue and COVID-19 in Asia: Experience from Indonesia.

The role of CD4+, CD8+, CD4+/CD8+ and neutrophile to lymphocyte ratio in predicting and determining COVID-19 severity in Indonesian patients.