Impact of COVID-19 Pandemic on Pre-Treatment Delays, Detection, and Clinical Characteristics of Tuberculosis Patients in Ningxia Hui Autonomous Region, China

Health system delay and risk factors in pulmonary tuberculosis diagnosis before and during the COVID-19 epidemic: a multi-center survey in China

Background

Understanding health system delay (HSD) in pulmonary tuberculosis (PTB) diagnosis aids in tailoring interventions for case detection and curbing transmission. However, recent nationwide studies on HSD in PTB diagnosis have been scarce. This study assesses HSD and its risk factors in China, taking into account the impact of the COVID-19 epidemic.

Methods

Patients diagnosed with PTB between 2019 and 2022 were selected using a multistage stratified clustering method. A semi-structured questionnaire was employed to assess HSD, which was defined as the interval between the patient's initial visit to a health facility and the definitive PTB diagnosis. The HSD was then compared between 2019 (before the epidemic) and 2020-2022 (during the epidemic). Factors associated with long health system delay (LHSD, defined as HSD > 14 days) were examined using both univariate and multivariate analyses with chi-square tests and binary logistic regression, respectively.

Results

In total, 958 patients with PTB were analyzed: 478 before and 480 during the epidemic. The HSD was 14 (interquartile range, 7-30) days for all patients, and the HSD before and during the epidemic also shared this value. A total of 199 patients (20.8%) had LHSD. LHSD was more prevalent in patients presenting solely with cough and expectoration (Odds ratio [OR]: 1.482, 95% confidence interval [CI]: 1.015-2.162) and those visiting ≥2 health facilities before definitive diagnosis (2 health facilities: OR = 2.469, 95%CI: 1.239-4.920; ≥3 health facilities: OR = 8.306, 95%CI: 4.032-17.111). Additionally, patients with negative bacteriological results were independently associated with higher LHSD risk (OR = 1.485, 95%CI: 1.060-2.080).

Conclusion

In China, HSD in PTB diagnosis remains relatively low and is primarily mediated by factors associated with health providers. No significant impact on HSD from the COVID-19 epidemic has been found. Implementing targeted training programs to enhance health providers' awareness of chronic respiratory symptoms and maintain vigilance for PTB; strengthening presumptive PTB identification capabilities at grassroots health facilities, and promoting the use of Mycobacterium tuberculosis (MTB) bacteriological technologies are recommended to shorten the HSD.

TB treatment delays and associated risk factors in Dushanbe, Tajikistan, 2019-2021

BACKGROUND

In Tajikistan, where there are about 8,000 cases annually, many new cases are being diagnosed with severe disease, indicating a delay in receiving care. We aimed to estimate the proportion with delayed care and the main factors contributing to delayed care.

METHODS

Using a retrospective cohort design, we conducted a study that included all people aged over 15 years who were newly diagnosed with pulmonary TB in Dushanbe from 2019 to 2021. We defined 'patient delay' as > 14 days from TB symptom onset to the first provider visit and 'provider delay' as > 3 days from the first visit to treatment initiation. Data was abstracted from medical records and participants were interviewed in-person. Multivariable negative binomial regression was used to estimate adjusted risk ratios (aRR) and 95% confidence intervals (CI).

RESULTS

Of 472 participants, 49% were male, 65% had lung tissue cavitation, 33% had drug resistant TB, 11% had diabetes, 4% had HIV, and. Reported cases dropped from 196 in 2019 to 109 in 2020 and increased to 167 in 2021. The proportion of people experiencing patient delays was 82%, 72%, and 90% per year, respectively. The proportion of provider delays was 44%, 41% and 29% per year. Patient delay was associated with year (aRR: 1.09 [CI:1.02-1.18] in 2021 vs. 2019), age (aRR:0.91 [0.82-0.99] for 40-59-year-olds vs. 15-39-year-olds), having HIV (aRR:1.22 [1.08-1.38]), having blood in sputum (aRR:1.19 [1.10-1.28]), chest pain (aRR:1.32 [1.14-1.54]), having at least two structural barriers vs. none (aRR:1.52 [1.28-1.80]), having one of the following barriers: long wait lines (aRR:1.36 [1.03-1.80]), feeling that healthcare services were expensive (aRR:1.54 [1.28-1.85]), or having no time or too much work (aRR:1.54 [1.29-1.84]). Provider delay was associated with year (aRR: 0.67 [0.51-0.89] in 2021 vs. 2019), patients having to pay for X-ray services (aRR: 1.59 [1.22-2.07]) and lacking direct-observed-therapy (DOTS) in facility (aRR: 1.61 [1.03-2.52]).

CONCLUSIONS

Patient delay was high before the COVID-19 pandemic and increased in 2021, while provider delay decreased during this time. Addressing structural barriers to healthcare services, such as increased DOTS facilities, expanded hours, and zero fees, may decrease delays.

Understanding the impact of pandemics on long-term medication adherence: directly observed therapy in a tuberculosis treatment cohort pre- and post-COVID-19 lockdowns

BACKGROUND

The COVID-19 pandemic negatively impacted tuberculosis (TB) treatment services, including directly observed therapy (DOT) programs used to promote medication adherence. We compared DOT adherence embedded in a research study before and after COVID-19 lockdowns in South Africa.

METHODS

We analyzed data from 263 observational study participants undergoing drug susceptible (DS)-TB DOT between May 2017 to March 2022. Participants enrolled before October 2019 were considered 'pre-COVID-19' and those enrolled after September 2020 were considered 'post-COVID-19 lockdown groups. Negative binomial regression models were used to compare DOT non-adherence rates between the two lockdown groups. We then conducted a sensitivity analysis which only included participants enrolled in the immediate period following the first COVID-19 lockdown.

RESULTS

DOT non-adherence rate was higher in the post-COVID-19 lockdown group (aIRR = 1.42, 95% CI = 1.04-1.96; p = 0.028) compared to pre-COVID-19 lockdown period, adjusting for age, sex, employment status, household hunger, depression risk, and smoked substance use. DOT non-adherence was highest immediately following the initial lockdown (aIRR = 1.74, 95% CI = 1.17-2.67; p = 0.006).

CONCLUSION

The COVID-19 lockdowns adversely effected adherence to TB DOT in the period after lockdowns were lifted. The change in DOT adherence persisted even after adjusting for socioeconomic and behavioral variables. We need a better understanding of what treatment adherence barriers were exacerbated by COVID-19 lockdowns to improve outcomes in post-pandemic times.

TRIAL REGISTRATION

ClinicalTrials.gov Registration Number: NCT02840877. Registered on 19 July 2016.

Case fatality among people with drug-susceptible TB enrolled in a private health sector TB treatment support program in Bihar, India during the first year of the COVID-19 pandemic

Experiencing 27% of the global tuberculosis (TB) burden, India's TB epidemic is the largest in the world. Due to COVID-19-related disruptions to TB programs, India has also seen the largest drop in TB case notifications of any country globally. We estimated case fatality among people treated for TB in India during the pandemic and compared these to pre-pandemic estimates. A random sample of 4,000 adults enrolled in World Health Partners (WHP), a private sector TB treatment support program (enrolling only people with drug-susceptible TB) in Bihar, India in the first year of COVID-19 (Mar 2020-Mar 2021) were contacted via phone to collect information on TB case fatality and other relevant covariates. Inverse probability of selection (IPS) weighting was used to obtain selection-bias-corrected in-treatment and post-treatment case fatality estimates. Covariates associated with (but not necessarily causal of) case fatality were identified by estimating adjusted hazard ratios (HRs) using the Cox proportional hazards model. WHP enrolled 19,826 adult drug-susceptible TB patients in the first year of COVID-19 (Mar 2020 to Mar 2021). Of our random sample of 4,000 patients, n = 2,962 (74.1%) answered the follow-up call. Unweighted and IPS-weighted in-treatment case fatality in the primary analysis were 6.12% (95%CI: 5.31-6.97%) and 6.07% (95%CI: 5.22-6.93%), respectively. Post-treatment case fatality estimates were 0.97% (95%CI: 0.61-1.33%) (unweighted) and 1.27% (95%CI: 0.79-1.79) (IPS-weighted). Our IPS-weighted estimates for in-treatment and post-treatment case fatality were similar to pre-pandemic IPS-weighted estimates (in-treatment: 7.27%, 95%CI: 5.97%- 8.49% and 12 months post-treatment: 1.23, 95%CI: 0.75-1.73). Although not higher than pre-pandemic estimates, the observed case fatality in this private sector cohort of people treated for drug-susceptible TB during COVID-19 in Bihar, India is above the level needed to reach the 2025 and 2030 End TB Strategy targets for reductions in TB deaths, underlining the extent of pandemic-related setbacks to TB elimination.

Predicting the incidence of rifampicin resistant tuberculosis in Yunnan, China: a seasonal time series analysis based on routine surveillance data

BACKGROUND

Rifampicin resistant tuberculosis (RR-TB) poses a growing threat to individuals and communities. This study utilized a seasonal autoregressive integrated moving average (SARIMA) model to quantitatively predict the monthly incidence of RR-TB in Yunnan Province which could guide government health administration departments and the centers for disease control and prevention (CDC) in preventing and controlling the RR-TB epidemic.

METHODS

The study utilized routine surveillance reporting data from the infectious Disease Network Surveillance and Reporting System. Monthly incidence rates of RR-TB were collected from January 2019 to December 2022. A time series SARIMA model was used to predict the number of monthly RR-TB cases in Yunnan Province in 2023, and the model was validated using time series plots, seasonal and non-seasonal differencing, autocorrelation and partial autocorrelation analysis, and white noise tests.

RESULTS

From 2019 to 2022, the incidence of RR-TB decreases as the incidence of all TB decreases (P < 0.05). There was no significant change in the proportion of RR-TB among all TB cases, which remained within 2.5% (P>0.05). The time series decomposition shows that it presented obvious seasonality, periodicity and randomness after being decomposed. Time series analysis was performed on the original series after 1 non-seasonal difference and 1 seasonal difference, the ADF test showed P < 0.05. According to ACF and PACF, the SARIMA (1, 1, 1) (1, 1, 0)12 model was chosen and statistically significant model parameter estimates (P < 0.05). The predicted seasonal trend of RR-TB incidence in 2019 to 2023 was similar to the actual data. The percentage accuracy in the prediction excesses 80% in 2019 to 2022 and is all within 95% CI. However there was a certain gap between the actual incidence and the predicted value in 2023, and the acutual incidence had increased by 12.4% compared to 2022. The percentage of accuracy in the prediction was only 70% in 2023.

CONCLUSIONS

We found the incidence of RR-TB was based on that of all TB in Yunnan. The SARIMA model successfully predicted the seasonal incidence trend of RR-TB in Yunnan Province in 2019 to 2023, but the prediction precision could be influenced by factors such as new infectious disease outbreaks or pandemics, social issues, environmental challenges or other unknown risks. Hence CDCs should pay special attention to the post epidemic effects of new infectious disease outbreaks or pandemics, carry out monitoring and early warning, and better optimize disease prediction models.

The global impact of COVID-19 on tuberculosis: A thematic scoping review, 2020-2023

BACKGROUND

This thematic scoping review of publications sought to understand the global impact of COVID-19 on tuberculosis (TB), interpret the scope of resonating themes, and offer policy recommendations to stimulate TB recovery and future pandemic preparedness.

DATA SOURCES

Publications were captured from three search engines, PubMed, EBSCO, and Google Scholar, and applicable websites written in English from January 1, 2020, to April 30, 2023.

STUDY SELECTION

Our scoping review was limited to publications detailing the impact of COVID-19 on TB. Original research, reviews, letters, and editorials describing the deleterious and harmful--yet sometimes positive--impact of COVID-19 (sole exposure) on TB (sole outcome) were included. The objective was to methodically categorize the impacts into themes through a comprehensive review of selected studies to provide significant health policy guidance.

DATA EXTRACTION

Two authors independently screened citations and full texts, while the third arbitrated when consensus was not met. All three performed data extraction.

DATA SYNTHESIS/RESULTS

Of 1,755 screened publications, 176 (10%) covering 39 countries over 41 months met the inclusion criteria. By independently using a data extraction instrument, the three authors identified ten principal themes from each publication. These themes were later finalized through a consensus decision. The themes encompassed TB's care cascade, patient-centered care, psychosocial issues, and health services: 1) case-finding and notification (n = 45; 26%); 2) diagnosis and laboratory systems (n = 19; 10.7%) 3) prevention, treatment, and care (n = 22; 12.2%); 4) telemedicine/telehealth (n = 12; 6.8%); 5) social determinants of health (n = 14; 8%); 6) airborne infection prevention and control (n = 8; 4.6%); 7) health system strengthening (n = 22; 13%); 8) mental health (n = 13; 7.4%); 9) stigma (n = 11; 6.3%); and 10) health education (n = 10; 5.7%).

LIMITATIONS

Heterogeneity of publications within themes.

CONCLUSIONS

We identified ten globally generalizable themes of COVID-19's impact on TB. The impact and lessons learned from the themed analysis propelled us to draft public health policy recommendations to direct evidence-informed guidance that strengthens comprehensive global responses, recovery for TB, and future airborne pandemic preparedness.

Analysis on time delay of tuberculosis among adolescents and young adults in Eastern China

Background

Tuberculosis (TB) is recognized as a significant global public health concern. Still, there remains a dearth of comprehensive evaluation regarding the specific indicators and their influencing factors of delay for adolescents and young adults.

Methods

All notified pulmonary TB (PTB) patients in Jiaxing City were collected between 2005 and 2022 from China's TB Information Management System. Logistic regression models were conducted to ascertain the factors that influenced patient and health system delays for PTB cases, respectively. Furthermore, the impact of the COVID-19 pandemic on local delays has been explored.

Results

From January 1, 2005 to December 31, 2022, a total of 5,282 PTB cases were notified in Jiaxing City, including 1,678 adolescents and 3,604 young adults. For patient delay, female (AOR: 1.18, 95%CI: 1.05-1.32), PTB complicated with extra-pulmonary TB (AOR: 1.70, 95% CI: 1.28-2.26), passive case finding (AOR: 1.46, 95% CI: 1.07-1.98) and retreatment (AOR: 1.52, 95% CI: 1.11-2.09) showed a higher risk of delay. For health system delay, minorities (AOR: 0.69, 95% CI: 0.53-0.90) and non-students (AOR: 0.83, 95% CI: 0.71-0.98) experienced a lower delay. Referral (AOR: 1.46, 95% CI: 1.29-1.65) had a higher health system delay compared with clinical consultation. Furthermore, county hospitals (AOR: 1.47, 95% CI: 1.32-1.65) and etiological positive results (AOR: 1.46, 95% CI: 1.30-1.63) were associated with comparatively high odds of patient delay. Contrarily, county hospitals (AOR: 0.88, 95% CI: 0.78-1.00) and etiological positive results (AOR: 0.67, 95% CI: 0.59-0.74) experienced a lower health system delay. Besides, the median of patient delay, health system delay, and total delay during the COVID-19 pandemic were significantly lower than that before.

Conclusion

In general, there has been a noteworthy decline in the notification rate of PTB among adolescents and young adults in Jiaxing City while the declining trend was not obvious in patient delay, health system delay, and total delay, respectively. It also found factors such as gender, case-finding method, and the hospital level might influence the times of seeking health care and diagnosis in health agencies. These findings will provide valuable insights for refining preventive and treatment strategies for TB among adolescents and young adults.

Patient, Diagnosis, and Treatment Delays Among Tuberculosis Patients Before and During COVID-19 Epidemic - China, 2018-2022

What is already known about this topic?

The coronavirus disease (COVID-19) pandemic could have a damaging impact on access to tuberculosis (TB) diagnosis and treatment.

What is added by this report?

The overall delay experienced by TB patients during the COVID-19 pandemic has shown a modest decrease in comparison to the period before the pandemic. Notably, higher patient delays were observed among agricultural workers and those identified through passive case-finding methods. Furthermore, the patient delay in eastern regions was shorter compared to western and central regions.

What are the implications for public health practice?

The observed increase in patient delay in 2022 should be of concern for ongoing TB control efforts. Health education and active screening initiatives must be enhanced and broadened among high-risk populations and regions characterized by extended patient delays.

Impact of the COVID-19 pandemic on tuberculosis patients and tuberculosis control programs in Turkey, review and analysis

BACKGROUND

Many infectious diseases, including Tuberculosis (TB), have been put in the background with the COVID-19 pandemic. This study aimed to evaluate the changes in the number of TB patients, the parameters of the TB patients and tuberculosis control programs in the first year of the COVID-19 pandemic in Turkey when compared to the previous year.

METHODS

All TB patients who were recorded in Samsun province between March 1, 2019 and February 28, 2021 were included in this retrospective study. The data were analyzed in 2 groups as the COVID-19 period (March 2020 and February 2021) and the Pre-COVID-19 period (March 2019 and February 2020),the demographic and microbiological characteristics of the tuberculosis patients in both periods were compared according to months and years p < 0.05 was considered statistically significant.

RESULTS

The total number of TB patients was 320, although it was 172 in the Pre-COVID-19 period, it was 148 in the COVID-19 pandemic period. It was found that the TB incidence rate (IR) was 15.32%, the total number of examinations performed in TB dispensary decreased 33.54%, and the total number of contact examinations decreased by 53.54% during the pandemic period. The mean age of the patients decreased significantly during the COVID-19 period (p = 0.047), and it was found that culture positivity rates and smear positivity rates increased compared to the previous year (7.97%, p = 0.166, 1.86%; p = 0.507, respectively). SARS-CoV-2 PCR test result was found to be (-) in 46 (82.1%) of the 56 TB patients who were examined.

CONCLUSIONS

In the present study, it was found that the incidence of TB, the number of examinations, and the number of contact examinations decreased at significant levels. The decrease in TB patients was mostly in the first 3 months when COVID-19 precautions and restrictions were intense. As a conclusion, it was observed that the application of TB patients to the healthcare institution and TB control were affected negatively by the COVID-19 pandemic.

Influence of COVID-19 for delaying the diagnosis and treatment of pulmonary tuberculosis-Tianjin, China

Background

The COVID-19 pandemic has disrupted the diagnosis, treatment, and care for tuberculosis (TB). Delays in seeking TB care may result in increased community transmission and unfavorable treatment outcomes. We sought to understand the influence of the COVID-19 pandemic on the proportion of patients with TB who delayed seeking the diagnosis and care for TB and explore the reasons for their postponement.

Methods

We surveyed a representative sample of outpatients treated for pulmonary TB from June to November 2020 using an anonymous standardized questionnaire. Multivariable logistic regression was used to calculate adjusted odds ratios (aOR) and 95% confidence intervals (CIs) of factors associated with the postponement of TB care. We used routinely collected surveillance data to assess trends of TB reports before and after the emergence of COVID-19 (2017-2019 vs. 2020-2022) in Tianjin, China.

Results

Among 358 participants who were diagnosed with pulmonary TB during the COVID-19 response, 61 (17%) postponed seeking TB diagnosis due to COVID-19, with 39 (64%) citing fear as the primary reason. Female sex (aOR:2.0; 95% CI: 1.1-3.7), previous antituberculosis treatment (aOR:3.2; 95%CI: 1.4-7.6), and TB diagnosis during the first-level response (aOR = 3.2, 1.7-6.2) were associated with the postponement. Among all 518 participants receiving antituberculosis treatment, 57 (11%) had postponed their regular healthcare visits due to COVID-19, 175 (34%) received no treatment supervision, and 32 (6%) experienced treatment interruption. Compared to 2017-2019, reported pulmonary TB declined by 36.8% during the first-level response to COVID-19, 23.5% during the second-level response, 14% during the third-level response in 2020, and 4.3% in 2021.

Conclusion

The COVID-19 response reduced the number of people who sought and received diagnosis, treatment, and care for TB in Tianjin, China. Integrative programs to ensure access and continuity of TB services should be considered and dual testing for SARS-CoV-2 and M. tuberculosis may facilitate finding cases.

The impact of the COVID-19 pandemic on patients’ experiences obtaining a tuberculosis diagnosis in Peru: a mixed-methods study

Background

The COVID-19 pandemic disrupted TB services worldwide, leading to diagnostic delays. There have been few published reports describing how the pandemic affected people’s pathway to diagnosis from their own perspectives. We sought to evaluate the impact on the pandemic on people’s experiences obtaining a TB diagnosis.

Methods

We performed a mixed-methods study, enrolling newly diagnosed TB patients from 12 health centers in Lima, Peru. We used structured surveys to quantify diagnostic delay, defined as the time between symptom onset and diagnosis, and in-depth interviews to understand the ways in which the pandemic affected the pathway to care. We compared diagnostic delay between patients enrolled during the first year of the pandemic to those diagnosed after using a Wilcoxon rank-sum test. We used an inductive content analysis approach to analyze interview content related to the pandemic.

Results

We enrolled 51 patients during November 2020–April 2021 (during the first year of the pandemic) and 49 patients during October 2021–February 2022. Median diagnostic delay was longer for patients diagnosed during the first year of the pandemic (median 15 [IQR 5–26] weeks compared to 6 [IQR 3–18] weeks, p = 0.027). Qualitative analysis of 26 interviews revealed that the pandemic affected participants’ care-seeking behavior and their ability to access to TB diagnostic services, particularly for those diagnosed in the first year of the pandemic. Many participants initially had their symptoms attributed to COVID-19, resulting in delayed TB evaluation and additional costs for COVID-19 treatment.

Conclusions

The COVID-19 pandemic impacted multiple steps in the pathway to care for TB patients in Lima, causing delays in TB diagnosis. These findings demonstrate how the shifting of health care resources to prioritize COVID-19 can lead to collateral damage for people with TB and other conditions.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12879-022-07832-2.

Real-world association of adherence with outcomes and economic burden in patients with tuberculosis from South Korea claims data

Objectives: We analyzed tuberculosis (TB)-related costs according to treatment adherence, as well as the association between treatment adherence, treatment outcomes, and costs related to drug-susceptible TB in South Korea. Methods: Patients who had newly treated TB in South Korea between 2006 and 2015 were selected from nationwide sample claims data and categorized into adherent and non-adherent groups using the proportion of days TB drugs covered. Patients were followed-up from the initiation of TB treatment. The mean five-year cumulative costs per patient were estimated according to adherence. Moreover, we evaluated the relative ratios to identify cost drivers such as adherence, treatment outcomes, and baseline characteristics using generalized linear models. Four treatment outcomes were included: treatment completion, loss to follow-up, death, and the initiation of multidrug-resistant TB treatment. Results: Out of the 3,799 new patients with TB, 2,662 were adherent, and 1,137 were non-adherent. Five years after initiating TB treatment, the mean TB-related costs were USD 2,270 and USD 2,694 in the adherent and non-adherent groups, respectively. The TB-related monthly cost per patient was also lower in the adherent than in the non-adherent (relative ratio = 0.89, 95% CI 0.92-0.98), while patients who were lost to follow-up spent more on TB-related costs (2.52, 2.24-2.83) compared to those who completed the treatment. Conclusion: Non-adherent patients with TB spend more on treatment costs while they have poorer outcomes compared to adherent patients with TB. Improving patient adherence may lead to effective treatment outcomes and reduce the economic burden of TB. Policymakers and providers should consider commitment programs to improve patient's adherence.

Application of the ARIMA Model in Forecasting the Incidence of Tuberculosis in Anhui During COVID-19 Pandemic from 2021 to 2022

Objective

Forecasting the seasonality and trend of pulmonary tuberculosis is important for the rational allocation of health resources. In this study, we predict the incidence of pulmonary tuberculosis by establishing the autoregressive integrated moving average (ARIMA) model and providing support for pulmonary tuberculosis prevention and control during COVID-19 pandemic.

Methods

Registered tuberculosis(TB) cases from January 2013 to December 2020 in Anhui province were analysed using traditional descriptive epidemiological methods. Then we used the monthly incidence rate of TB from January 2013 through June 2020 to construct ARIMA model, and used the incidence rate from July 2020 to December 2020 to evaluate the forecasting accuracy. Ljung Box test, Akaike's information criterion(AICc), Bayesian information criterion(BIC) and Realtive error were used to evaluate the model fitting and forecasting effect, Finally, the optimal model was used to forecast the expected monthly incidence of tuberculosis for 2021 and 2022 to learn about the incidence trend.

Results

A total of 255,656 TB cases were registered. The reported rate of tuberculosis was highest in 2013 and lowest in 2020. The peak incidence was in March, Tongling (71.97/100,000), Chizhou (59.93/100,000), and Huainan (58.36/100,000) had the highest number of cases. The ratio of male to female incidence was 2.59:1, with the largest proportion of people being between 66 and 75 years old. The main occupation of patients was farmer. ARIMA (0, 1, 1) (0, 1, 1)₁₂ model was the optimal model to forecast the incidence trend of TB.

Conclusion

Tongling, Chizhou, and Huainan should strengthen measures for TB. In particular, the government should pay more attention on elderly people to prevent tuberculosis infections. The rate of TB patient registration and reporting has decreased under the pandemic of COVID-19. The ARIMA model can be a useful tool for predicting future TB cases.

Increased Healthcare Delays in Tuberculosis Patients During the First Wave of COVID-19 Pandemic in Korea: A Nationwide Cross-Sectional Study

BACKGROUND

The coronavirus disease 2019 (COVID-19) pandemic caused disruptions to healthcare systems, consequently endangering tuberculosis (TB) control. We investigated delays in TB treatment among notified patients during the first wave of the COVID-19 pandemic in Korea.

METHODS

We systemically collected and analyzed data from the Korea TB cohort database from January to May 2020. Groups were categorized as 'before-pandemic' and 'during-pandemic' based on TB notification period. Presentation delay was defined as the period between initial onset of symptoms and the first hospital visit, and healthcare delay as the period between the first hospital visit and anti-TB treatment initiation. A multivariate logistic regression analysis was performed to evaluate factors associated with delays in TB treatment.

RESULTS

Proportion of presentation delay > 14 days was not significantly different between two groups (48.3% vs. 43.7%, P = 0.067); however, proportion of healthcare delay > 5 days was significantly higher in the during-pandemic group (48.6% vs. 42.3%, P = 0.012). In multivariate analysis, the during-pandemic group was significantly associated with healthcare delay > 5 days (adjusted odds ratio = 0.884, 95% confidence interval = 0.715-1.094).

CONCLUSION

The COVID-19 pandemic was associated with healthcare delay of > 5 days in Korea. Public health interventions are necessary to minimize the pandemic's impact on the national TB control project.

Cut-off Points of Treatment Delay to Predict Poor Outcomes Among New Pulmonary Tuberculosis Cases in Dalian, China: A Cohort Study

Purpose

Despite increasing literature on the association between treatment delay and outcomes, cut-off point (1 month or median) selection in almost all studies for treatment delay is too subjective. This study explored more scientific cut-off points of treatment delay for poor treatment outcomes and death at the clinical level.

Patients and Methods

A total of 18,100 newly confirmed pulmonary tuberculosis (TB) cases in Dalian, China were used in the final analysis. A 3-knotted restricted cubic spline (RCS) fitted for Cox proportional hazard regression models is used to analyse the effects of cut-off points of treatment delay on incident poor treatment outcomes. To explore the moderating effects of age, gender and diabetes, we added the interaction terms of these moderating variables and treatment delay to Cox proportional hazard regression models.

Results

The median time of treatment initiation was 30 days (IQR: 14–59 days). The risk of incident poor treatment outcomes increased when the time was greater than cut-off point 1 (53 days; adjusted HR: 1.26; 95% CI: 1.00–1.60) of treatment delay, and the risk of incident death events increased when the time was greater than cut-off point 2 (103 days; adjusted HR: 1.56; 95% CI: 1.00–2.44) of delay. In addition, treatment delay was associated with an increased risk of incident poor treatment outcomes and death, and older age, male sex, and diabetes may increase the risk of treatment delay for poor outcomes.

Conclusion

This study is the first to identify scientific cut-off points of treatment delay for poor treatment outcomes and death, and this method of exploration should be popularized. In addition, the knowledge of tuberculosis must be spread to every adult. Moreover, the tuberculosis diagnosis level of community level health workers should be enhanced.