key: cord-0859930-14hk274c
authors: Dey, Abhijit; Roy, Isita; Chakrabartty, Arup Kumar; Choudhury, Anuradha; Lahiri, Arista
title: Changing patterns of household transmission of Tuberculosis in an Eastern state of India: The impact of COVID19 pandemic
date: 2022-03-11
journal: Indian J Tuberc
DOI: 10.1016/j.ijtb.2022.03.001
sha: 726c2160bf4716ad6467b1f50e8cdbb5acdf88ca
doc_id: 859930
cord_uid: 14hk274c

BACKGROUND: The COVID-19 Pandemic has affected many components of the Tuberculosis (TB) control program. Due to lockdown and restrictions, people, including TB patients, might have spent more time in the household. There might be an increased TB transmission among the household contacts (HHC). The current study was conducted to measure the household transmission of TB and also find out the relationship with several clinico-social factors. METHODS: Contact tracing data of West Bengal, India, was extracted from Nikshay portal of Central TB Division, Government of India. The anonymized data was divided into two parts, firstly before the lockdown initiation in India and secondly during the lockdown. A modified Poisson regression model was developed to determine the statistical association between clinico-social variables and the pandemic with household-level secondary TB cases. RESULTS: There was a 30% reduction in daily TB case notification, but the proportion of HHC screened was 4% higher during the pandemic than the pre-pandemic period. The secondary attack rate of household TB disease transmission was 34% lower during the pandemic period. Index TB patients aged under ten years, microbiologically positive, Drug-Resistant TB, having three or more HHCs, treatment delay more than seven days, notified from the private sector, and diagnosis during the pre-pandemic period was found to be independently associated with a higher risk of having a secondary TB case at household. CONCLUSION: The risk of household TB transmission was significantly lower during the pandemic period compared to the pre-pandemic period, which may be due to better infection prevention and control practices.

Tuberculosis (TB) is one of the oldest endemic diseases affecting humanity. It remains the major public health problem of concern even today, with an estimated incidence of 10 million and 1.5 million deaths globally each year [1, 2] . The world has seen an unprecedented pandemic due to the novel coronavirus disease at the beginning of 2020, which has impacted every health program, and the TB program is not an exception [3] [4] [5] [6] [7] . We know from previous epidemics that reduced access to care, medicines, and diagnostics for people with lifethreatening conditions, such as TB, can increase deaths from these underlying conditions [8] .

Historically, significant disruptions such as natural disasters, war, and infectious disease pandemics have compromised TB programs and increased the TB burden [9, 10] . There are reports of considerable disruption in TB service provisions due to the ongoing pandemic in both primary care and hospital settings [11, 12] . The pandemic-led disruptions of TB services in India can significantly increase TB morbidity and mortality [13] .

To prevent household TB transmission, the World Health Organization (WHO) recommended a systematic process of screening intended to identify previously undiagnosed cases of TB among the contacts of an index case, and TB Preventive Therapy (TPT) for the children after ruling out active TB [14] . TPT is the treatment offered to individuals who are considered at risk of TB disease in order to reduce that risk. Despite the recommendation and the country's implementation efforts, it is evident that the contact screening status in India has been suboptimal over the years [15] [16] [17] [18] . Moreover, due to the COVID19-related lockdown and restrictions on social gatherings, there is reduced access to health services like contact screening and TPT. People, including TB patients, are likely to spend more time in their households for obvious restriction norms. So, there might be an increased TB transmission among the household contacts (HHC) of the TB patients. An HHC is defined as a person who shared the same enclosed living space as the index case for one or more nights or frequent or extended daytime periods during the three months before the start of current treatment [19] .

Studies have reported the socio-demographic and other associations of the contacts (infectee) who eventually become TB patients [20] [21] [22] [23] [24] . But there is a dearth of studies that have assessed the socio-demographic and other associations of the index TB patients (infector) who eventually produce a secondary case within the household. Also, no such study compared the TB transmission rate among household contacts during this pandemic with the pre-pandemic era to the best of our knowledge. Therefore, we conducted this study to compare the household J o u r n a l P r e -p r o o f transmission of TB in West Bengal, India, during the pre-pandemic period and the pandemic.

We also determined the associations of different relevant socio-clinical factors of the index TB patient with transmission at the household level.

We conducted a secondary data analysis using the contact tracing data of West Bengal available from the Nikshay portal [25] . All notified TB patients (the index cases) were retrospectively followed up as per the data available to see the household incidence of secondary TB cases. The relevant contact tracing data is available from the database of the Nikshay portal. We retrieved these data from January 1, 2019, to June 30, 2021 (910 days). 

West Bengal, a major state in the Eastern part of India, is the fourth most populous state.

Our analysis considered all the 2,34,657 TB patients diagnosed in West Bengal and notified in the Nikshay portal from January 1, 2019, to June 30, 2021. In the first stage of analysis, all these patients were included. Among the notified TB patients, we found index TB patients who do not have any HHC and several index TB patients where none of the HHCs were screened for TB symptoms. These cases were excluded during the second stage of analysis. Among the remaining TB patients, there were cases where some of the HHCs have been put on TPT. We also excluded these patients from our analysis to eliminate the heterogeneity of risk. Thus, the final sample size was 1,22,385 TB patients with at least one HHC with all HHCs screened and no HHC given TPT. The flow of participant selection is depicted in Figure 1. 

The principal author (AD) extracted the required data from the contact tracing register from January 2019 to June 2021 by accessing the Nikshay portal for records from West Bengal[25].

In the anonymized dataset "Episode ID" was used as unique identifier during the data curation J o u r n a l P r e -p r o o f & analysis process. The date of diagnosis, the basis of diagnosis, date of treatment initiation, age, gender, site of disease, type of TB, type of notification, number of above six years old & under six years old HHC, number of HHC screened for TB, number of HHC diagnosed with TB, and the number of beneficiaries put on TPT were the key variables extracted from the database. The socio-demographic information of the index TB patients was also extracted. For the purpose of our analysis, we considered the phase (pre-pandemic or during pandemic) of TB notification of the index patient as a predictor variable. We considered age, gender, site of disease, basis of diagnosis, type of notification, duration from diagnosis till treatment initiation, TB treatment regimen, and the number of household contacts as other variables in our study.

The data were analyzed using STATA 14.2 (StataCorp LP, College Station, TX, USA). At the first stage, the TB diagnosis and notification indicators were calculated. To calculate the mean number of HHCs per index TB patient, we took the ratio of the total number of HHCs notified and the total number of index TB patients with at least one HHC. Socio-demographic and clinical characteristics were assessed separately for any statistical difference during the pandemic and pre-pandemic periods for all index TB patients and index TB patients with at least one secondary infection in the household. Chi-squared tests determined the bivariate statistical associations. In the second stage of our analysis, we tested for the factors contributing to household TB transmission. The bivariate association between the factors and diagnosis of a secondary case were assessed separately with negative binomial regression models. For multivariate analysis, a modified Poisson regression model with robust standard errors was used to evaluate the independent associations of the socio-demographic and clinical characteristics of index TB patients with the diagnosis of a secondary case in the household and calculate the adjusted relative risk (aRR) with 95% confidence interval (95% CI).

The current study was a secondary data analysis of the data available from the government database. The analysis involved review of the anonymized patient records extracted (i.e., the program-level data). Therefore, the need for ethical clearance was waived. We maintained confidentiality during the handling and analysis of the dataset extracted.

J o u r n a l P r e -p r o o f

Among the total 234657 TB patients, 136451 patients were notified during the Prepandemic phase at an average of 305 cases per day. On the other hand, 98206 patients were notified during the pandemic at an average of 213 cases per day. The proportion of reduction in notification was 30%. Total HHCs identified were 723687, of which 87% were screened for TB symptoms. Proportion HHC screened during the pre-pandemic period was 86%, whereas 90% during the pandemic. Overall, Secondary Attack Rate (SAR) was 4.15 (95% CI: 4.13-4.16) per thousand HHC. SAR was 4.77 (95% CI: 4.76 -4.79) before the pandemic, whereas it was 3.14 (95% CI: 3.12 -3.16) during the pandemic. The details regarding TB cases notification and contact identification are provided in Table 1 .

The mean age of the index TB Patients was 39.7 (± 17.5) years, and 67.8% were males.

78.1% were Pulmonary TB & 73.0% were microbiologically confirmed. The proportion of Private notification was 17.9% & drug-resistant TB was 4.5%. The mean duration from diagnosis to Treatment initiation was 2.4 (± 0.9) days, and the mean number of HHC was 5.1 (± 1.5) per index TB patient. 67.5% of such patients were notified before lockdown. Of the 122385 index TB patients identified, 1417 (1.16%, 95% CI: 1.10%-1.22%) patients had at least one HHC infected with TB. The socio-demographic & clinical profile of the Index TB Patients & the TB patients who have at least one secondary TB patient before & during the pandemic has been compared and summarized in Table 2 . Table 3 shows the factors associated with having a secondary TB patient in the household. 

The findings from our study represent the scenario of a large state in India and are relevant from the policy perspective also. It was observed that there was a 30% reduction in daily TB Whatever may be the reason, the findings strongly suggest that TPT should be extended to HHC of EPTB patients.

Microbiological confirmation, having three or more HHC, and treatment delay of more than seven days was found to be associated with having a secondary case at household. These Index TB patients notified from the private sector were associated with a 17% higher risk of having a secondary case in the household. TB management practices in India's private sector are heterogeneous and often suboptimal [34] [35] [36] [37] . Delayed diagnosis, delayed treatment initiation, poor treatment adherence of the index patient might have caused a higher proportion of HHC infected with TB. NTP must take utmost care of private-sector TB patients, especially for public health action, which is one of the most neglected parts of TB care in the private sector.

Index cases diagnosed in the pre-pandemic period were found to be independently associated with having a secondary case at household with a 27% extra-risk compared to the TB patient notified during the pandemic period. Widespread use of masks, sanitizer, social distancing & other IPC practices might have contributed to lower risk during the pandemic.

Due to the COVID19 pandemic, the barriers associated with face mask use have waned off significantly. The TB patients, as a result, are now consistently wearing the mask, which was not consistent before the pandemic due to the self-perceived stigma [38, 39] . This might be leading to less household transmission & eventually a reduction in overall TB incidence.

Literature reported or forecasted similar findings [40, 41] .

This study is one of the first studies in India to assess the impact of COVID-19 on household TB transmission empirically. Our study utilized data obtained under programmatic settings and reflects the field realities. The study has a relatively large sample size and reflects the whole State of West Bengal scenario during the referenced period. Fourth, the robust study design to measure the strength of association. To minimize heterogeneity in risk measurements, we excluded TB patients who did not have HHC or had HHC put on TPT or HHC not screened for TB. We have used data from Nikshay, which is believed to be very trusted data as it is being validated at different stages of the data cycle, starting from entry to archiving. But being a secondary data analysis, it does not provide any information regarding the quality of the contact tracing process and the portal. Since the routine data collected did not include potential confounders like socioeconomic status, overcrowding, malnourishment or other comorbidities, household pollution, distance from the health facility, education level of the index TB patients, we could not adjust our model for their effects. We assumed that the HHCs have equal exposure and from only one Index TB patient, which though computationally efficient, but maybe different in reality. We have considered the occurrence of TB disease (active TB disease) among HHC to measure TB transmission within the household & we could not detect the TB infection (erstwhile Latent TB Infection), which could have been a perhaps better indicator to measure actual TB transmission. Thus, the factors associated with having a secondary case in the household have to be interpreted with caution.

Based on the study findings, we came up with specific action points for effective contact management under the NTP and further containing the spread of TB in the community. 

The risk of TB transmission among the household contacts was significantly lower during the pandemic period compared to the pre-pandemic period. Due to Covid, the stigma associated J o u r n a l P r e -p r o o f 

J o u r n a l P r e -p r o o f 

Drug Susceptible TB

PE Interpreting the decline in tuberculosis: the role of secular trends in effective contact

Central TB Division: Directorate General of Health Services Advisory from DDG-TB to mitigate the impact of COVID-19 pandemic on NTEP

Tuberculosis in the era of COVID-19 in India

The potential impact of the COVID-19 pandemic on the tuberculosis epidemic a modelling analysis

World Health Organization (WHO) Guidance for National Tuberculosis Programmes on the management of tuberculosis in children -an update. Available online: www.who.int (accessed on

Tuberculosis screening in household contacts of pulmonary tuberculosis patients in an urban setting

Isoniazid preventive treatment in children in two districts of South India: Does practice follow policy?

Evaluation of TB Case Finding through Systematic

Contact Investigation

Isoniazid preventive therapy among children living with tuberculosis patients: Is it working? A mixed-method study from Bhopal, India

World Health Organization (WHO) WHO consolidated guidelines on tuberculosis. Module 1: Prevention -tuberculosis preventive treatment

Prevalence and risk factors for transmission of infection among children in household contact with adults having pulmonary tuberculosis

Prevalence and Associated Factors of Tuberculosis among Adult Household Contacts of Smear Positive Pulmonary Tuberculosis Patients Treated in Public Health Facilities of Haramaya District

Contact investigation for tuberculosis: A systematic review and meta-analysis

Tuberculosis in Household Contacts of Infectious Cases in Kampala, Uganda

How do urban indian private practitioners diagnose and treat tuberculosis? A cross-sectional study in Chennai

Tuberculosis management by private practitioners in Mumbai, India: Has anything changed in two decades?

Quality of tuberculosis care in the private health sector

Treatment adherence status of the TB patients notified from private sector and its associated factors: Findings of a secondary data analysis from West Bengal

Directorate General of Health Services: Government of India Strategy to End Stigma and Discrimination Associated with Tuberculosis Available online

Face masks in the post-COVID-19 era: a silver lining for the damaged tuberculosis public health response?

Drug Resistant TB

All other numbers within the parentheses from the subsequent rows indicate column percentages for each category. TB= Tuberculosis, HHC= Household contact

J o u r n a l P r e -p r o o f