• Users Online: 148
  • Print this page
  • Email this page

 
Table of Contents
ORIGINAL ARTICLE
Year : 2021  |  Volume : 10  |  Issue : 4  |  Page : 162-168

Dynamics of transmission of COVID-19 cases and household contacts: A prospective cohort study


1 Department of Community Medicine, Jubilee Mission Medical College and Research Institute, Thrissur, Kerala, India
2 Department of Psychiatry, Jubilee Mission Medical College and Research Institute, Thrissur, Kerala, India

Date of Submission17-Jun-2021
Date of Decision09-Jul-2021
Date of Acceptance13-Jul-2021
Date of Web Publication20-Jul-2021

Correspondence Address:
Praveenlal Kuttichira
Department of Psychiatry, Jubilee Mission Medical College and Research Institute, Thrissur, Kerala
India
Login to access the Email id

Source of Support: None, Conflict of Interest: None


DOI: 10.4103/2221-6189.321590

Get Permissions

  Abstract 

Objective: To study the transmission dynamics of coronavirus disease 2019 (COVID-19) among 101 confirmed cases and their 387 household contacts and to determine risk factors associated with secondary attack among the household contacts.
Methods: A prospective cohort study was conducted from January 1st 2021 to February 28th 2021, among 101 SARS-CoV-2 cases and 387 household contacts who were followed up for 14 days from the last day of contact with the index case of COVID-19. The dynamics of disease transmission was estimated, and factors affecting transmission risk were analyzed. Besides, the association between various factors and household secondary attack rate was determined.
Results: The median incubation period was found to be 5 days, and the observed reproductive number (R) was found to be 1.63 (95% CI: 1.28-1.98). The mean household secondary attack rate was 40.7%. Contacts with comorbidities like diabetes mellitus, hypertension, dyslipidemia, and hypothyroidism had significantly higher attack rates (P<0.05).
Conclusions: As new variants of SARS-CoV-2 emerges, it is crucial to know the trasmission dynamics. This study shows a high secondary attack rate of COVID-19 among household contacts that must be closely monitored.

Keywords: Dynamics; Transmission; COVID-19; Kerala; Prospective cohort


How to cite this article:
Rajmohan P, Jose P, Thodi JB, Thomas J, Raphael L, Krishna S, Gopinathan UU, Kuttichira P. Dynamics of transmission of COVID-19 cases and household contacts: A prospective cohort study. J Acute Dis 2021;10:162-8

How to cite this URL:
Rajmohan P, Jose P, Thodi JB, Thomas J, Raphael L, Krishna S, Gopinathan UU, Kuttichira P. Dynamics of transmission of COVID-19 cases and household contacts: A prospective cohort study. J Acute Dis [serial online] 2021 [cited 2021 Jul 30];10:162-8. Available from: http://www.jadweb.org/text.asp?2021/10/4/162/321590


  1. Introduction Top


The coronavirus disease (COVID-19) pandemic continues to spread globally[1]. It has been reported in more than two hundred countries and territories, causing millions of deaths. Given the overwhelming influence of the disease, COVID-19 was declared a pandemic on March 11st, 2020, by the World Health Organization[2]. On 30th January 2020, the first case of COVID-19 was reported in our city, Thrissur, India from a student who returned from abroad[3]. Since then, the disease has spread to over 93 611 176 people and caused 2 004 431 deaths across the globe[4]. The symptoms of COVID-19 are fever, tiredness, cough, sore throat, breathing difficulty, loss of smell, runny nose, or diarrhea[5]. Since the emergence of the disease, there was a swift response from the scientific community worldwide, attempting to fathom out its major epidemiological and clinical characteristics. A variant of SARS-CoV-2 with a D614G substitution in the gene encoding the spike protein lineage known as B.1.1.7 emerged in late October 2020 in U.K. Studies in human respiratory cells and animal models demonstrated that compared to the initial virus strain, the strain with the D614G substitution has increased infectivity and transmission[6].



It may be remembered that the Spanish flu, yellow fever, etc. could be controlled with public health approaches, though not eradicated. Understanding the epidemiology of communicable diseases could help develop appropriate public health strategies in a way that facilitates control measures more rapidly and effectively. Thus, studying the pattern and magnitude of the spread of communicable diseases contributes to strategy development.

The natural history and dynamics of transmission of this new wave of COVID-19 can be studied if the cases are identified early and the primary contacts are meticulously traced. Although studies have been done in this domain of COVID-19, emerging variations in the genetic characteristics of the virus and subsequent variations in the transmission dynamics as evidenced by high transmission rates of the second wave of the pandemic in India demand ongoing region-specific research. A carefully designed follow-up study of COVID-19 cases and their high-risk primary contacts would help provide estimates of the median incubation period, serial interval, observed reproductive number, and secondary attack rate specific to our region. Here, we traced 101 COVID-19 cases and their 387 high-risk household contacts, from January 2021 and followed them up to March 2021 to determine the dynamics of transmission of the second wave of COVID-19 and to describe its clinical-epidemiological characteristics.


  2. Patients and methods Top


2.1. Study design and patients

A prospective cohort study was conducted from January 1st 2021 to March 31st 2021 among confirmed cases of COVID-19 and their household contacts.

All patients who attended our hospital with symptoms suggestive of COVID-19 or having a history of contact with confirmed SARS-CoV-2 cases from January 1st, 2021 to February 28th, 2021 were tested for SARS-CoV-2 either by real-time RT PCR (TeqPath COVID-19 CE-IVD RT-PCR kit, Thermo fisher scientific, USA) or Rapid Antigen Test (Meriscreen COVID-19 antigen detection test kit, Meril Diagnostics, India). A confirmed case is defined as a clinical suspect with positive detection of SARS-CoV-2 nucleic acid by real-time RT-PCR or qualitative detection of SARS-CoV-2 antigen using rapid immunochromatographic assay test (COVID-19 antigen detection test). Confirmed cases were categorized as category A, B, or C according to the clinical categorization guidelines by the directorate of health services, the government of Kerala[7], and were isolated and treated in hospital or advised home isolation as per the clinical category.

2.2. Ethical approval

The study is approved by the Institutional Ethics Committee of Jubilee Mission Medical College and Research Institute, Thrissur, Kerala, India (39/21/IEC/JMMC&RI).

2.3. Contact tracing and epidemiological investigation

The household primary contacts of the index case were identified through contact tracing. Household contacts were defined as family members who live in the same house and had interacted with the index case from 48 h before symptom onset to the day the index case is isolated. The contacts were followed up for a period of 14 d from the last day of contact with the index case for any symptoms suggestive of COVID-19. Those contacts that developed symptoms and found to be COVID-19 positive were further followed up for two more weeks.

2.4. Study tools and data collection

Data was collected using a structured interview schedule consisting of questions on demographic and clinical details of index cases and their household contacts. The dynamics of COVID-19 transmission among the contacts was studied by closely monitoring the confirmed cases and their close household contacts for the development of symptoms.

Based on the close follow-up of all the household contacts of each index case, the incubation period was calculated as the time interval between the last day of contact with the index case and the appearance of the first symptom of COVID-19. Serial interval is calculated as the time interval between symptom onset in the index cases and their infected contacts. The household secondary attack rate was calculated as the percentage of household contacts that were later confirmed to have SARS-CoV-2 infection. The observed reproductive number (R) of COVID-19 was calculated as the mean number of secondary cases caused by each index case.

2.5. End points

Primary end points: To estimate the median incubation period, serial interval, observed reproductive number, and secondary attack rate of COVID-19.

Secondary end point: To determine risk factors associated with secondary attack among the household contacts.

2.6. Statistical analysis

Data were coded and entered into Microsoft Excel and analyzed using IBM SPSS version 25. Qualitative data are expressed as frequency and proportion and quantitative data as the median and interquartile range (IQR). The association between various factors and household secondary attack rate was analyzed using Chi-square tests and binary logistic regression method.


  3. Results Top


From January 1st, 2021, to February 28th, 2021, we identified 101 index cases and their 387 household contacts. The majority of the index cases were females (77.23%), but there were a higher proportion of males (52.97%) among household contacts. For the median age (interquartile range) of the study population, index cases, and household contacts were 32 (19-52), 33 (27-41), and 32 (15-55) years respectively. Adults (18-65 years) comprised the maximum proportion of the index cases (97%) and household contacts (60.7%). Among the index cases, 89% were employed, and among the contacts, 72.9% were unemployed [Table 1].
Table 1: Socio-demographic characteristics and clinical profile of the index cases and primary contacts.

Click here to view


Among the 387 household contacts of the index cases, 165 (42.6%) tested positive for SARS-CoV-2; Among them, 77 (46.6%) were females, and 88 (53.3%) were males. Only 4.95% of index cases were asymptomatic, whereas, 23.64% were asymptomatic among household contacts. The early symptoms among index cases were fever (41.7%), myalgia (13.5%), headache (12.5%), rhinitis (10.4%), sore throat (5.2%), fatigue (4.2%) and loss of smell and taste (4.2%). The early symptoms in household contacts were fever (56.3%), cough (9.5%), headache (9.5%), sore throat (8.7%), myalgia (5.6%), fatigue (1.6%), rhinitis (63%) and loose stools (1.6%) [Figure 1].
Figure 1: Early symptoms of index cases and primary contacts. LST: Lost of smell and taste.

Click here to view


The median incubation period (time taken for 50% of the household contacts to develop symptoms following exposure to the index case) was found to be 5 d (95% CI: 4.45-5.55). Serial interval (time interval between symptom onset in the index cases and their infected contacts) was found to be 3 d (95% CI: 2.45-3.55). The proportion of cases who developed symptoms of SARS-CoV-2 by days after infection is depicted in [Figure 2].
Figure 2: The proportion of cases who developed symptoms of SARS-CoV-2 by days after infection.

Click here to view


The observed reproductive number (R) was calculated using individual level contact tracing of the 101 index cases, and it was found to be 1.63 (95% CI: 1.28-1.98). The mean household secondary attack rate was 40.7%. In 40 households none of the close contacts were tested positive for COVID-19, whereas in 27 households, all the close contacts were tested positive [Figure 3].
Figure 3: Secondary attack rate among the household contacts.

Click here to view


Children below the age of 5 years and individuals in the age group of 18-65 showed similar attack rates (44.9% and 45.1%, respectively) [Figure 4].
Figure 4: Attack rate among household contacts by age group.

Click here to view


Contacts with comorbidities like diabetes mellitus, hypertension, dyslipidemia and hypothyroidism had significantly higher attack rates [Table 2]. There were 37 households with household secondary attack rate more than 50%. Households which consisted of two or more members in the vulnerable age group (<10 years and above 60 years) were categorized as high risk households. It was observed that the attack rate was similar in both groups [Table 3].
Table 2: Secondary attack rate and its risk factors among primary contacts.

Click here to view
Table 3: Household characteristics and secondary attack rate.

Click here to view


The COVID-19 positive cases and contacts were followed up for a period of 14 d after their Rapid Antigen test turned negative for the presence of any persisting symptoms. Among them, 24 (14.5%) complained about persistence of symptoms. The most common persisting symptom was anosmia [5 (20.8%)] and [myalgia 5 (20.8%)], followed by fatigue, headache and cough.


  4. Discussion Top


We did a prospective study to find out the transmission dynamics and epidemiological characteristics of COVID-19 among the cases and their household contacts from January to March 2021. In our study we traced 387 high risk contacts of the 101 index cases. As fever was the most common symptom, 41.7% of index cases and 56.3% of the primary contacts had history of fever. Other symptoms like Myalgia, headache, rhinitis, sore throat, loose stools were also reported. In a study by Bhandari et al.[8] cough was the most common symptom followed by fever, myalgia, headache and dyspnea. According to studies by Wang et al., and Guan et al.[9],[10], it was found that fever was the most common symptom which is consistent with our findings. In our study the median incubation period was found to be 5 d (95% CI: 4.45-5.55). In a meta-analysis study done by Quesada et al. they found the mean incubation period was 5.6 d, where the lowest value reported was 5.0 d which is consistent with our finding[11],[12],[13].

R0 represents the average number of people infected by one infectious individual. If R0 is greater than 1, it denotes the number of infected people is likely to increase and is an early warning signal for an epidemic or pandemic[14]. The observed reproductive number (R) in our study was calculated using individual level contact tracing of the 101 index cases and it was found to be 1.63 (95% CI: 1.28-1.98). According to recent reports, India’s effective reproductive number, which is a measure of how fast an infection spreads, has dropped to 0.92, but shows a rise in the second wave of the pandemic due to the mutant strain. In studies done earlier, Zhao et al. estimated the mean basic reproduction number (R0) of SARS-CoV-2 to range between 2.24 and 3.58 and Imai et al. reported it is 2.6, in the early phase of the outbreak[15],[16]. In a study done by Shah et al. they found out that secondary attack rate varies widely across countries with lowest reported rate as 4.6% and highest as 49.56% in India, consistent with our finding of the household secondary attack rate of 40.7%[17]. Thus, the rates may be immune from confounders such as population of the country, lockdown status and geographic location. The review also suggests greater vulnerability in spouse and elderly population for secondary transmission than other household members, and they also observed that quarantining and isolation are most effective strategies for prevention of the secondary transmission of the disease, and the symptomatic status of the index case is an important factor in determining the transmission probability[17]. A study by Jing et al. found out that SARS-CoV-2 was more transmissible in households than SARS-CoV and MERS-CoV, and elderly were most vulnerable for household transmission. It is not possible to contain the pandemic by case finding and isolation alone, but need to integrate with strict restriction of human movement[18]. In our study those households where index cases were isolated at home showed a significantly higher household secondary attack rate as compared to those who were isolated and treated in hospitals. This result implies that the patinets who were isolated at home need practice adequate social distancing and other preventive measures strictly at home and monitored periodically by government authorities.

We found out that those who have comorbidities like diabetes mellitus, hypertension, dyslipidemia and hypothyroidism had significantly higher attack rates than those who didn’t have any comorbidity. According to the Health Ministry data, Government of India, while 53% deaths were reported among 60-year-old and above, 35% deaths were recorded in the age group of 45-60 years, 10% aged 26-44 years and 1% in the age group of 18-25 years and below 17 years. In the age group of 45-60 years, 13.9% had comorbidities and 1.5% had no comorbidity. Among the patients below 45 years of age, those with comorbidities accounted for 8.8% of the fatalities while 0.2% did not have any comorbidity. The overall case fatality rate is 15 times higher in those with comorbidities. Several meta-analyses studies have reported the prevalence of comorbidities in patients with COVID-19[19],[20],[21]. In a study done by Singh et al., recent meta-analysis that included 18 studies (n=14 558) from China, USA and Italy after carefully excluding the overlapped studies, have reported a prevalence of hypertension in 22.9%, diabetes in 11.5%, CVD in 9.7%, cancer in 3.9%, COPD in 3.1% in patients with COVID-19[22].

Being a single center study, the index cases included only those reported to our center with symptoms suggestive of COVID-19. In addition, only those contacts who undergone testing and provided information about their symptoms and other personal information to the contact tracing team were followed up. These factors could be considered as limitations against generalizations. Our hospital caters to low and middle socio-economic categories of patients, which could affect their household characteristics. This factor coupled with the closed study setting, might have resulted in an overestimation of secondary attack rate compared to population level estimates.

SARS-CoV-2 is continuing to spread across the globe in an alarming state. Thus, it is crucial to expand our knowledge about the transmission dynamics of this disease. Prospective studies with data on meticulous contact tracing and identification of source of infection are useful for estimating critical values such as incubation period and observed reproductive number. These estimates are expected to provide inputs for setting up public health policies and interventions to curb further spread of the disease.

Conflict of interest statement

The authors report no conflict of interest.

Authors’ contributions

The project was conceptualized by P.R.; The literature searches and data collection were performed by P.R. and P.J.; The manuscript was written by P.R., P.J. and J.A.T.; Data management and analysis was done by J.T. and U.U.G.; The manuscript was critically reviewed and edited by L.R., S.K. and P.K.

 
  References Top

1.
Ng SL, Soon TN, Yap WH, Liew KB, Lim YC, Ming LC, et al. Convalescent plasma: A potential therapeutic option for COVID-19 patients. Asian Pac J Trop Med 2020; 13(11): 477-486.  Back to cited text no. 1
    
2.
World Health Organization. Coronavirus disease 2019 (COVID-19) situation reports. [Online] Available from: https://www.who.int/ emergencies/diseases/novelcoronavirus-2019/situation-reports. [Accessed on February 23rd 2021].  Back to cited text no. 2
    
3.
The Lancet. India under COVID-19 lockdown. Lancet 2020; 395(10233): 1315.  Back to cited text no. 3
    
4.
Webmeter. COVID-19-age, sex, demographics Worldometer 2020. [Online] Available from: http://www.worldometers.info. [Accessed on February 8th 2021].  Back to cited text no. 4
    
5.
Symptoms of COVID-19. Centre for disease control and prevention. [Online] Available from: https://www.cdc.gov/coronavirus/2019-ncov/ symptoms-testing/symptoms.html. [Accessed on February 22rd 2021].  Back to cited text no. 5
    
6.
The effects of virus variants on COVID-19 vaccines. COVID-19 virus variants. World Health Organization.2021. [Online] Available from: https://www.who.int/csr/don/31-december-2020-sars-cov2-variants/en/. [Accessed on March 11th 2021].  Back to cited text no. 6
    
7.
Department of Health & Family Welfare Government of Kerala. COVID-19 clinical management report. [Online] Available from: https://dhs.kerala.gov.in/wp-content/uploads/2020/07/Report-COVID-Clinical-Managment.pdf. [Accessed on February 4th 2021].  Back to cited text no. 7
    
8.
Bhandari S, Bhargava A, Sharma S, Keshwani P, Sharma R, Banerjee S. Clinical profile of COVID-19 infected patients admitted in a tertiary care hospital in north India. J Assoc Physicians India 2020; 68(5): 13-17.  Back to cited text no. 8
    
9.
Wang D, Hu B, Hu C, Zhu FF, Liu X, Zhang J, et al. Clinical characteristics of 138 hospitalized patients with 2019 novel coronavirus-infected pneumonia in Wuhan, China. JAMA 2020; 323(11): 1061-1069.  Back to cited text no. 9
    
10.
Guan WJ, Ni ZY, Hu Y, Chen XT, Ao YL, Fitzpatrick T, et al. Clinical characteristics of Coronavirus Disease 2019 in China. N Engl J Med 2020; 382(18): 1708-1720.  Back to cited text no. 10
    
11.
Quesada JA, López-Pineda A, Gil-Guillén VF, Arriero-Marín JM, Gutiérrez F, Carratala-Munuera C. Incubation period of COVID-19: A systematic review and meta-analysis. Rev Clin Esp (Barc) 2021; 221(2): 109-117.  Back to cited text no. 11
    
12.
Linton NM, Kobayashi T, Yang Y, Hayashi K, Akhmetzhanov AR, Jung SM, et al. Incubation period and other epidemiological characteristics of 2019 novel coronavirus infections with right truncation: A statistical analysis of publicly available case data. J Clin Med 2020; 9(2): 538.  Back to cited text no. 12
    
13.
Tian S, Hu N, Lou J, Chen K, Kang XQ, Xiang ZJ, et al. Characteristics of COVID-19 infection in Beijing. J Infect 2020; 80(4): 401-406.  Back to cited text no. 13
    
14.
Song QQ, Zhao H, Fang LQ, Liu W, Zheng C, Zhang Y. Study on assessing early epidemiological parameters of COVID-19 epidemic in China. Zhonghua Liu Xing Bing Xue Za Zhi 2020; 41(4): 461-465.  Back to cited text no. 14
    
15.
Zhao S, Lin Q, Ran J, Musa SS, Yang G, Wang W, et al. Preliminary estimation of the basic reproduction number of novel coronavirus (2019-nCoV) in China, from 2019 to 2020: A data-driven analysis in the early phase of the outbreak. Int J Infect Dis 2020; 92: 214-217.  Back to cited text no. 15
    
16.
Imai N, Dorigatti I, Cori A, Donnelly C, Riley S, Ferguson NM. Report 2: Estimating the potential total number of novel Coronavirus (2019-nCoV) cases in Wuhan City, China. Imperial College London COVID-19 Response Team. [Online] Available from: https://www.imperial.ac.uk/ media/imperial-college/medicine/sph/ide/gida-fellowships/Imperial-College-COVID19-update-epidemic-size-22-01-2020.pdf. [Accessed on November 18th 2020].  Back to cited text no. 16
    
17.
Shah K, Saxena D, Mavalankar D. Secondary attack rate of COVID-19 in household contacts: a systematic review. QJM 2020; 113(12): 841-850.  Back to cited text no. 17
    
18.
Jing QL, Liu MJ, Yuan J, Zhang ZB, Zhang AR, Dean NE, et al. Household secondary attack rate of COVID-19 and associated determinants. medRxiv 2020; doi: 10.1101/2020.04.11.20056010.  Back to cited text no. 18
    
19.
Li B, Yang J, Zhao F, Zhang ZB, Zhang AR, Dean NE, et al. Prevalence and impact of cardiovascular metabolic diseases on COVID-19 in China. Clin Res Cardiol 2020; 109(5): 531-538.  Back to cited text no. 19
    
20.
Yang J, Zheng Y, Gou X, Ke Pu, Chen ZF, Guo QH, et al. Prevalence of comorbidities and its effects in patients infected with SARS-CoV-2: a systematic review and meta-analysis. Int J Infect Dis 2020; 94: 91-95.  Back to cited text no. 20
    
21.
Emami A, Javanmardi F, Pirbonyeh N, Akbari A. Prevalence of underlying diseases in hospitalized patients with COVID-19: A systematic review and meta-analysis. Arch Acad Emerg Med 2020; 8(1): e35.  Back to cited text no. 21
    
22.
Singh AK, Gillies CL, Singh R, Singh A, Chudasama Y, Coles B, et al. Prevalence of co-morbidities and their association with mortality in patients with COVID-19: A systematic review and meta-analysis. Diabetes Obes Metab 2020; 22(10): 1915-1924.  Back to cited text no. 22
    


    Figures

  [Figure 1], [Figure 2], [Figure 3], [Figure 4]
 
 
    Tables

  [Table 1], [Table 2], [Table 3]



 

Top
 
  Search
 
    Similar in PUBMED
   Search Pubmed for
   Search in Google Scholar for
 Related articles
    Access Statistics
    Email Alert *
    Add to My List *
* Registration required (free)  

 
  In this article
Abstract
1. Introduction
2. Patients and ...
3. Results
4. Discussion
References
Article Figures
Article Tables

 Article Access Statistics
    Viewed76    
    Printed0    
    Emailed0    
    PDF Downloaded9    
    Comments [Add]    

Recommend this journal