Contagious diseases have emerged as a main indi-catory factors of poverty and poor health status in  developing and under-developed countries (Kumar et al., 2007). In 2018 & 2019, dengue viral epidemic in Bangladesh affected the ability and strength of working people to carry on with day to day activities. In many countries, dengue is a public health problems (Okanurak et al., 1997). The term “Dengue” was first originated in Zanzibar naming “Denga” during 1870 epidemic (Mahmood & Mahmood, 2011). The dengue virus usually spreads by day biting female Aedes mos-quitoes, primarily Aedes aegypti and Aedes albopictus (Sharmin et al., 2015). Climate change will increase severity of dengue  in the future (Naish et al., 2014).

Bangladesh has made a noticeable progress in child mortality and maternity sector by developing primary healthcare access (Das & Horton, 2013). But so far, the overall public healthcare facilities are not standard to the public demand. Since most of the public hospitals lack medical documentation system and modern dia-gnostic facilities, continuous surveillance for dengue disease is a vast challenge here (Organization, 2015). In 1964, dengue was first reported in Dhaka, hence named after as “Dacca Fever” (Aziz et al., 1967). The fever remained epidemic since then (Ahmed et al., 2001).

Dhaka had been experiencing a large-scale dengue outbreak in every year since 2000 (Akram, 2019). The dengue epidemic in 2019 at Dhaka city created serious public health problem, causing significant absence in working place. Fig 1 shows how dengue emerged on a sudden large scale. The disease caused a huge economic and social burden in the city. In this paper, the socio-economic impact was measured through the number of absent days in working place of the affected people and percentage of monthly family income spend to monthly family expenditure for occurring dengue disease. The significant covariates for occur-ring this disease were identified and various sug-gestions for knocking the disease off had been analyzed, discussed and concluding remarks made. 

Primary data were collected from October 9 to November 20, 2019. For this purpose, a questionnaire was designed and data were collected by direct inter-view (face-to-face) method. Respondents were conve-niently selected from Dhaka city where dengue outbreak had occurred. The study covered 235 dengue affected and 235 unaffected respondents.   

The questionnaire involved seven major sections: personal (demographic) information of the respon-dents, economic condition, environmental condition, disease incidence, preventive measure, treatment, and suggestions. The variables that were highlighted in this study are: family cost [Percentage of monthly income spent on expenditure], incidence [no, yes], living status [alone, with family, with friends/colleague, others], family size, marital status [single, married, divorced, widowed, separated], economic status [lower class, lower middle, middle, higher middle, higher], absence [number of days absent from work], age [0-15, 15-30, 30-45, 45-60, 60+], gender [male, female, others], treatment cost, education status [illiterate, primary, secondary, higher secondary, graduate], drainage system [bad, medium, good], providing spray by city corporation [no, yes], and area [university area, resi-dential area, slum, crowded area, VIP area, commer-cial area, industrial area, hostel area, others].  

Regression analysis is an important statistical method to investigate the relationships that exist between a dependent variable and a set of independent variables (Draper & Smith, 1998; Zeileis & Hothorn, 2002). This widely used analysis examines which factors matter most, which factors can be neglected, and how these factors influence each other (Fahrmeir et al., 2013; Montgomery et al., 2012). Regression techn-iques for making predictions is drive by three techniques mostly: type of dependent variables, number of independent variables, and shape of the regression line (Seber & Lee, 2012). However, two widely used regression model, multiple linear reg-ression and binary logistic regression, had been considered here. If independent variable is more than one and dependent variable is continuous type having linear relationship with independent variables and follows some other specific assumptions then multiple linear regression model can assess the impact of independent variables on dependent variable (Nathans et al., 2012). For the vector of covariatesx and vector of response variable Y, the form of the multiple linear regression model in matrix notation becomes (Brown, 2009)

Y=x^ β+ϵ,

Where,β and ϵ be the vector of regression coefficient and random error term, respectively. If the response vector Y be of binary type, that is, referring to whether an event of interest has occurred or not, binary logistic regression is used for modeling purpose, which has the following functional form (Sarkar & Midi, 2010).

π(x)=e^(x^ β)/(1+e^(x^ β) )

Where,π(x) represents the conditional mean of Y given xi.e., E(Y| x). In both models, the unknown parameters (β) are estimated by the method of maxi-mum likelihood estimation (Albert & Anderson, 1984; Myung, 2003). Here, the former model applied for relating family cost and productivity to dengue inci-dence, while the factors for occurring dengue disease was identified by the later model. Also, multiple response analysis had been incorporated to assess various suggestions from patients.

Model 1

The impact of dengue infection on the monthly expenditure of the patient was determined by the first model (multiple linear regression models). In this model, dependent variable family cost [percentage of monthly income spent on expenditure] was used as a proxy for measuring monthly expenditure of the patient. The main independent variable was dengue incidence and related covariates were also considered. The model had the form as –

Where,β denotes regression coefficient of the covariates and ϵ_i is the random error term of the i^th respondent. 

Model 2

The second model was also a multiple linear regression model which determined impact of dengue infection on human productivity. The dependent variable absence [number of days absent from work] was used as a proxy for measuring productivity of the patient. The main independent variable was dengue incidence with other related covariates. The model took the form as – 

Where,β and ϵ_i bear the same meaning as before. 

Model 3

Binary logistic regression applied for detecting risk factors of dengue disease. The acting dependent variable dengue incidence [whether dengue disease occurred or not], which was of binary type. This variable and related independent variables took the functional form as – 

Where,β and ϵ_i bear the same meaning as before. 

Fig 1: Year wise dengue cases in Dhaka (Data Source: Akram, 2019).

The Fig 1 is a clear indication of sudden increase of dengue affected people in Dhaka in 2019. Dengue patients increased from 2769 in 2017 to 10148 in 2018, then reached the highest record 16223 in 2019. This study attempted to explore the reasons behind and the impact made in socioeconomic life in Dhaka.  

Multiple linear regression and binary logistic regression models had been employed to analyze dengue patients data. The obtained results were shown in Table 1, Table 2, and Table 3. Table 1 presented the factors related to family cost. 

Table 1: Multiple linear regression model estimates of the selected covariates for family cost in Dhaka city along with standard error (SE) and p-value.

The obtained significant variables were living status, family size, marital status and economic status, while incidence was the only covariate that turned out as insignificant at 5% level of significance. Living “with others” decreased the percentage of monthly income spent on expenditure by 10.565 percent compared to living “alone” keeping all other covariates constant. Living with family has no significant effect compared to living alone at 5% significance. Extra one person increasing in number of family member increased the percentage of monthly income spent on expenditure by 2.363 percent. Percentage of monthly income spent on expenditure increased by 4.210 percent and decreased by 13.144 percent in the married and divorced patient groups, respectively, compared to the alone patient group keeping all other independent variables fixed. The lower middle, middle, higher middle, and higher economic class patients had 12.615, 8.102, 7.214, and 15.753 percent less monthly income spent on expenditure than lower economic class patients, respe-ctively. From Table 2, it is noticed that the covariates incidence, living status, and treatment cost were significantly affecting productivity, while family size, age, marital status and gender turned out as insignificant at 5% level of significance. 

Table 2: Multiple linear regression model estimates of the selected covariates for productivity in Dhaka city along with standard error (SE) and p-value.

Dengue incidence had significant effect on produ-ctivity of the patients with p-value less than 0.001. It hampered approximately 6 working days, keeping all other covariates fixed. Living status was significant at 10% significance level. Patients living with family remained 1.261 days less absent from workplace than patients living alone, keeping all other covariates constant. The positive value of the coefficient under treatment cost denoted more absence in workplace with the higher treatment cost. That is, the more a patient had to pay for dengue, the more he remained absent in workings (Shazeed-Ul-Karim, 2019). 

The risk factors that are acting behind to occur dengue fever were shown in Table 3. The variables living status, drainage system, providing spray, and area were found significant in Table 3 while gender, age, marital status, and education status were insignificant. 

Table 3: Binary logistic regression model estimates of the selected covariates for dengue incidence in Dhaka along with standard error (SE), hazard ratio (HR), and p-value.

The respondents living with family had 2.048 times significantly less odds of occurring dengue disease at 10% significance level than respondents living alone. The respondents provided with good drainage system had experienced 87.9% fewer odds compared to bad drainage system and this is highly significant at 1% level of significance having p-value 0.002. Providing spray in the locality was significant at 1% significance level with p-value 0.001 bringing 54.1% less odds of experiencing dengue disease compared to from not providing spray. The patients belonging to residential, VIP, and commercial area had significantly 1.653, 2.038, and 1.716 times less odds, respectively, of having this disease at 5% level of significance than patients from university area. 

Table 4: Multiple response analysis of used preventive approach of the dengue affected respondents in Dhaka city.

Multiple Response Analysis - Multiple response analysis is an analysis of frequency when more than one response can be obtained from each participant. Multiple responses had been arranged in three portions in this study: preventive approaches of dengue, suggestions about peoples steps on prevention of dengue, suggestions about governments steps on prevention of dengue. 

Table 4 showed that 5.5% patients who were affected by dengue didnt use any approach such as coil, aerosol, liquid, mosquito racket, net, etc. 44.1% patients used coil, 35.3% patients used aerosol, 17.5% of patients used liquid, 27.9% patients used mosquito racket and 57.8% patients used net as a preventive approach to protect from dengue. 

Table 5: Multiple response analysis of the suggestions regarding necessary steps that people might take to prevent dengue disease.

It was observed from Table 5 that 7.9%  people had no suggestions, 33.3% people preferred that they could cover tightly all water containers, 37.5%  people had opinion that they could burry unused tiers, 60.8% people wanted to keep drain free from blockage, 61.3% people could change water in plant container, 39.9% people preferred to change water in trays under the fridge, 29.9% people could destroy/burn unused containers, 65.1% people also said that they could use mosquito repellent and mosquito net when sleeping and 19.8% of people preferred to take others steps to prevent dengue fever transmission during outbreak. 

Table 6: Multiple response analysis of the suggestions regarding necessary steps that government might take to prevent dengue disease.

From Table 6, 42.8% people were found who thought that government could repair open manhole, 65.7% people wanted that government could develop the drainage system, 47.3% people preferred that gover-nment should remove blocked water source, 69.4% people wanted that government should provide regular mosquito spray, and 41.2% people suggested gover-nment should keep the locality clean.  

This paper primarily measured the impact of dengue both on society and economy.  It was observed that dengue had no significant effect on family expenditure. The underlying reason is that the treatment of dengue was not that expensive to affect the total family cost. But, this result contradicted some previous work (Clark et al., 2005; Halasa et al., 2012; Harving & Ronsholt, 2007). However, dengue fever badly affected the human productivity, which was similar to previous works on this disease (Bhavsar  et al., 2010; Halasa et al., 2012; Serufo et al., 1993). Since dengue had no direct economic impact but as it affected productivity, it might affect the national economy indirectly. Again, living status and treatment cost had significant effect on productivity, while living status, marital status, and economic status were significant to the family cost of the respondents. 

A self-collected dataset was analyzed through sophis-ticated statistical modeling approaches to suspect socio-economic impact of dengue. The analysis found no direct effect of dengue on family cost, but it affected productivity which in terms might affect economy. The analysis revealed that alone living group are in greater risk of dengue (Kularatne, 2015). It might be the case that living alone people didnt take enough protection against mosquito bite, hence experienced the fever. People with bad drainage system experienced dengue disease, which might happen for blocked drains that grew and reserved mosquitos (Singh, 2007). The result expressed that providing mosquito spray decreased dengue incidence which comply with previous literature (Chadee, 2013). The probability of being affected varied significantly by different areas (Pathirana et al., 2009). Cleanliness of living areas is a must for preventing the disease which was proven in literature (Pai et al., 2006).  From the multiple response analysis, it was observed that a few number of respondents used no preventive approach, while majority used mosquito net as preven-tive approach. Using mosquito net is effective,  as this practice was suggested in literature (Nalongsack, Yoshida, Morita, Sosouphanh, & Sakamoto, 2009). The respondents suggested mostly to use mosquito repellent and net, keep drain free from blockage, and regular changing water from plant container. They suggested government to provide mosquito spray and develop drainage system regularly.

Alone living people were more prone to experience the disease, which might occur due to their insincerity about this disease. So, the living alone persons need to increase their consciousness considering the seriousness of this disease. Drainage system is an important issue for a high densely populated capital like Dhaka city. Government should focus to have well developed systems for neat and clean drains in the capital. City Corporation should provide mosquito spray to a regular basis as it had significant influence to decrease dengue incidence. The magnitude of dengue was different at different areas. Respondents highly recommended using mosquito repellent and net during sleeping, changing water regularly from plant container, providing regular mosquito spray and developing drainage system in Dhaka city. People should become conscious enough about the disease remembering all of its hazards.

First and foremost, the author is grateful to Almighty Allah. The author is also thankful to anonymous reviewers and editors for their helpful comments and suggestions.

The author declares no conflict of interest.