%0 Journal Article
%@ 2328-8957
%A Sharif, Nadim
%A Opu, Rubayet Rayhan
%A Khan, Afsana
%A Saha, Tama
%A Masud, Abdullah Ibna
%A Naim, Jannatin
%A Velázquez Martínez, Zaily Leticia
%A Osorio García, Carlos Manuel
%A Alsuwat, Meshari A
%A Alzahrani, Fuad M
%A Alzahrani, Khalid J
%A De la Torre Díez, Isabel
%A Dey, Shuvra Kanti
%D 2025
%F uninimx:16580
%J Open Forum Infectious Diseases
%K Epidemiology, Co-infection, Dengue, COVID-19, Bangladesh
%T Clinical epidemiology of dengue and COVID-19 co-infection among the residents in Dhaka, Bangladesh, 2021-2023: A cross-sectional study
%U http://repositorio.unini.edu.mx/id/eprint/16580/
%X Background Co-infection of dengue and COVID-19 has increased the health burden worldwide. We found a significant knowledge gap in epidemiology and risk factors of co-infection in Bangladesh.  Methods This study included 2458 participants from Dhaka city from December 1, 2021, to November 30, 2023. We performed Kruskal-Walli’s test and χ2 test. Multivariable logistic regression was also performed.  Results Co-infection of dengue and COVID-19 was found among 31% of the participants. Co-prevalence of dengue and COVID-19 was found in higher frequency in Jatrabari (14%), and Motijhil (11%). Severe (65%, p-value 0.001) and very severe (78%, p-value 0.005) symptoms were prevalent among the participants aged >50 years. Long-term illness was prevalent among the participants with co-infection (35%, 95% CI 33%- 36%) and COVID-19 (28%, 95% CI 26%- 30%). Co-infected participants had a higher frequency of heart damage (31.6%, p-value 0.005), brain fog (22%, p-value 0.03), and kidney damage (49.3%, p-value 0.001). Fever (100%) was the most prevalent symptom followed by weakness (89.6%), chills (82.4%), fatigue (81.4%), headache (80.6%), feeling thirsty (76.3%), myalgia (75%), pressure in the chest (69.1%), and shortness of breath (68.3%), respectively. Area of residence (OR 2.26, 95% CI 1.96-2.49, p-value 0.01), number of family members (OR 1.45, 95% CI 1.08-1.87, p-value <0.001), and population density (OR 2.43, 95% CI 2.15-3.01, p-value 0.001) were associated with higher odds of co-infection. We found that coinfected participants had a 4 times higher risk of developing severe health conditions (OR 4.22, 95% CI 4.11-4.67, p-value 0.02).  Conclusions This is one of the early epidemiologic studies of co-infection of dengue and COVID-19 in Bangladesh.