Journal of Tropical Diseases & Public Health

The Dissimilarity of Attack Rate (AR) of SARS-CoV-2 Virus and Infection Fatality Risk (IFR) Across Different Divisions of Bangladesh

Probir Kumar Ghosh^* Bridge of Community Development Foundation (BCDF), Dhaka, Bangladesh
^*Correspondence: Probir Kumar Ghosh, Bridge of Community Development Foundation (BCDF), Dhaka, Bangladesh, Email:

Received: 23-May-2020 Published: 10-Jul-2020, DOI: 10.35248/2329-891X.20.8.352

Introduction

Though novel coronavirus disease 2019 (COVID-19) emerged during December 2019 in Wuhan city in China, Bangladesh reported its first case on March 8, 2020 [1]. Up to May 15, 2020, Directorate General of Health Services, Ministry of Health and Family Welfare, Government of Bangladesh has reported more than 20,000 confirmed cases by Reverse Transcription Polymerase Chain Reaction (RT-PCR) test, from all 8 divisions (Dhaka, Chittagong, Mymensingh, Barisal, Sylhet, Khulna, Rajshahi and Rangpur). The division is the first-level administrative structures in Bangladesh which is further divided into several districts. Bangladesh is the densely-population country with medium human development index (0.614) varies from division to division. Compared to Dhaka, other divisions have limited opportunities in terms of diagnosis and health care facilities. Each division has unique demographic and socioeconomic characteristics [2].

Understanding the patterns of COVID-19 outbreak throughout Bangladesh could assist public health and policy strategies to mitigate the ongoing COVID-19 disease transmission. Therefore, we aimed to investigate population characteristics, isolation bed capacities of hospitals and RT-PCR sample test performance across Bangladesh and assess the variation in the Attack Rate (AR), positivity rate and Infection Fatality Risk (IFR) related to COVID-19 patients in these divisions.

Methods

We used data from population demographic characteristics from the lasted Bangladesh population census conducted by the Bangladesh Bureau of Statistics (BBS) in 2011 [3]. The isolation bed capacities of hospitals, the number of hospitals facility, and the cumulative number of collected and RT-PCR tested samples for COVID-19, the number of positive patients, the number of deaths and the number of recovered patients were collected from Directorate General Health Service (DGHS), Ministry of Health and Family Welfare, Government of Bangladesh on May 15, 2020 [4].

We performed descriptive statistical analyses to calculate the COVID-19 sample test rate and the Attack Rate (AR) per million populations for each division. We also calculated the positivity rate among samples tested by using the formula as;

, [5,6] and calculated the proportion of recovered from COVID-19 among the positive patients by using the formula as;

The fatality risk is expressed as the risk of deaths among the SARS-CoV-2 virus infected patients using a formula as; [7-10].

Results

The total estimated population 2019 of Bangladesh is 164681600 [11]. Across the 8 divisions, the population density ranged from 1751 per square kilometers in Dhaka to 613 per square kilometre in Barisal division. The average household size ranged from 5.5 in Sylhet to 4.1 in Rajshahi division. The proportion of older adults (aged >50 years) was the lowest in Sylhet (12.57%) and highest in Dhaka (16.25%). The hospital facility rate per million populations was the highest in Barisal (186 hospitals) and lowest in Dhaka (129 hospitals). The number of prepared isolation beds per million population for COVID-19 was the highest in Sylhet (88 beds) and lowest in Dhaka (30 beds) (Table 1).

Table 1: Population characteristics and hospital facilities among Bangladesh.

As of May 15, there was inequality in the number of testing COVID-19 samples by RT-PCR per 100,000 populations (271 in Dhaka; 60 in Mymensingh; 43 in Rangpur; 39 in Chittagong; 39 in Sylhet; 34 in Khulna; 33 in Rajshahi; 30 in Barisal). The AR of COVID-19 per million populations was the highest in Dhaka (386) and lowest in Rajshahi (13). The positivity rate among the collected samples was the highest in Dhaka (14.2%) and Chittagong (13.2%) and the lowest in Rajshahi (4.1%). The IFR of patients with COVID-19 was the highest in Rajshahi (11%) and lowest in Barisal (2%) and Khulna (2%). The proportion of patients recovered from COVID-19 disease was the highest in Barisal (45%) and lowest in Chittagong (16%) (Figure 1).

Figure 1: Coronavirus disease 2019 (COVID-19) sample test rate, positivity rate, Attack Rate (AR) and Infection Fatality Risk (IFR) by divisions in Bangladesh.

Discussion and Conclusion

The AR of SARS-CoV-2 virus, number of samples tested, positivity rate and IFR disparities across Bangladesh is concerning. Dhaka, where the number of tested samples was the highest, had higher AR and positive rate compared to the other 7 divisions. Dhaka is the most overcrowded division with the highest number of older populations. In contrast, the AR and positivity rate were the lowest in Rajshahi, which is characterized by predominantly average household size and lower sample testing by RT-PCR. The spatial study in China has shown that the overcrowded provinces were more likely to be infected with SARS-CoV-2 virus than lower crowded provinces [12].

Prior analyses have shown the comorbidity in adult population and inequalities in accessing health care facilities across different divisions in Bangladesh. A previous study shows that the highest number of the older population with the comorbid condition live in Rajshahi, which might be one reason for higher IFR in Rajshahi [13]. Previous studies in other countries have shown that the older SARS-CoV-2 virus infected with comorbidities were more likely to die compared to young population [14-16].

This study has limited follow-up up to May 15, 2020. Demographic characteristics of COVID-19 patients were not available. The distribution of migrant workers from COVID-19 infected countries in different divisions is not known. The statistical hypothesis test was not performed for significant variability of the outcomes.

Further studies are needed to investigate whether the disparities of the burden of COVID-19 in the adult population and rural communities in Bangladesh.

Acknowledgement

We would like to express our sincere thanks to Directorate General Health and Service (DGHS), Ministry of Health and Family Welfare, Government of Bangladesh for sharing the COVID-19 outbreak data.

Author Contributions

Probir G wrote the manuscript.

Conflict of Interest

None declared.

Funding

The author(s) disclosed that no financial support was received from any organization for the work.

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