Project description:BackgroundIn response to the COVID-19 epidemic, China implemented a series of interventions that impacted tuberculosis (TB) control in the country.MethodsBased on routine surveillance data and questionnaires, the study analyzed TB notification, follow-up examinations, and treatment outcomes. The data were split into three phases in relation to outbreak, lockdown and reopen when the nationwide COVID-19 response started in 2020: control (11 weeks prior), intensive (11 weeks during and immediately after), and regular (4 additional weeks). Data from 2017-2019 were used as baseline.FindingsThe notified number of TB patients decreased sharply in the 1st week of the intensive period but took significantly longer to rebound in 2020 compared with baseline. The percentages of TB patients undergoing sputum examination within one week after 2 months treatment and full treatment course in the intensive period were most affected and decreased by 8% in comparison with control period. 75•2% (221/294) of counties reallocated CDC and primary health care workers to fight the COVID-19 epidemic, 26•9% (725/2694) of TB patients had postponed or missed their follow-up examinations due to travel restrictions and fear of contracting COVID-19.InterpretationIn the short term, the COVID-19 epidemic mostly affected TB notification and follow-up examinations in China, which may lead to a surge of demand for TB services in the near future. To cope with this future challenge, an emergency response mechanism for TB should be established.FundingNational Health Commission of China-Bill & Melinda Gates Foundation TB Collaboration project (OPP1137180).
Project description:The whole world is going through an unprecedented period during the pandemic of COVID-19. This pandemic has affected all aspects of daily life with far-reaching implications, especially in most aspects of healthcare. Practice of surgery across the globe is in a standstill as of now. When we restart surgical practices across world, we have to bring new protocols and practices in place to combat the transmission. This article discusses the major changes in surgical practice, which need to be brought in. This article is based on scientific information about transmission of virus and experiences of some of the authors from China, a country which successfully dealt with and contained the virus outbreak.
Project description:BackgroundRecently, more patients who recovered from the novel coronavirus disease 2019 (COVID-19) may later test positive for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) again using reverse transcription-polymerase chain reaction (RT-PCR) testing. Even though it is still controversial about the possible explanation for clinical cases of long-term viral shedding, it remains unclear whether the persistent viral shedding means re-infection or recurrence.MethodsSpecimens were collected from three COVID-19-confirmed patients, and whole-genome sequencing was performed on these clinical specimens during their first hospital admission with a high viral load of SARS-CoV-2. Laboratory tests were examined and analyzed throughout the whole course of the disease. Phylogenetic analysis was carried out for SARS-CoV-2 haplotypes.ResultsWe found haplotypes of SARS-CoV-2 co-infection in two COVID-19 patients (YW01 and YW03) with a long period of hospitalization. However, only one haplotype was observed in the other patient with chronic lymphocytic leukemia (YW02), which was verified as one kind of viral haplotype. Patients YW01 and YW02 were admitted to the hospital after being infected with COVID-19 as members of a family cluster, but they had different haplotype characteristics in the early stage of infection; YW01 and YW03 were from different infection sources; however, similar haplotypes were found together.ConclusionThese findings show that haplotype diversity of SARS-CoV-2 may result in viral adaptation for persistent shedding in multiple recurrences of COVID-19 patients, who met the discharge requirement. However, the correlation between haplotype diversity of SARS-CoV-2 virus and immune status is not absolute. It showed important implications for the clinical management strategies for COVID-19 patients with long-term hospitalization or cases of recurrence.
Project description:The coronavirus disease 2019 (COVID-19) pandemic, caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has created a remarkable and varying impact in every country, inciting calls for broad attention. Recently, the Bacillus Calmette-Guérin (BCG) vaccination has been regarded as a potential candidate to explain this difference. Herein, we hypothesised that the past epidemic of Mycobacterium tuberculosis (M. tuberculosis) may act as a latent explanatory factor for the worldwide differences seen in COVID-19 impact on mortality and incidence. We compared two indicators of past epidemic of M. tuberculosis, specifically, incidence (90 countries in 1990) and mortality (28 countries in 1950), with the mortality and incidence of COVID-19. We determined that an inverse relationship existed between the past epidemic indicators of M. tuberculosis and current COVID-19 impact. The rate ratio of the cumulative COVID-19 mortality per 1 million was 2.70 (95% confidence interval [CI]: 1.09-6.68) per 1 unit decrease in the incidence rate of tuberculosis (per 100,000 people). The rate ratio of the cumulative COVID-19 incidence per 1 million was 2.07 (95% CI: 1.30-3.30). This association existed even after adjusting for potential confounders (rate of people aged 65 over, diabetes prevalence, the mortality rate from cardiovascular disease, and gross domestic product per capita), leading to an adjusted rate ratio of COVID-19 mortality of 2.44, (95% CI: 1.32-4.52) and a COVID-19 incidence of 1.31 (95% CI: 0.97-1.78). After latent infection, Mycobacterium survives in the human body and may continue to stimulate trained immunity. This study suggests a possible mechanism underlying the region-based variation in the COVID-19 impact.
Project description:BackgroundThe COVID-19 pandemic has driven public health intervention strategies, including keeping social distance, wearing masks in crowded places, and having good health habits, to prevent the transmission of the novel coronavirus (SARS-CoV-2). However, it is unknown whether the use of these intervention strategies influences morbidity in other human infectious diseases, such as tuberculosis.MethodsIn this study, three prediction models were constructed to compare variations in PTB incidences after January 2020 without or with intervention includes strict and regular interventions, when the COVID-19 outbreak began in China. The non-interventional model was developed with an autoregressive integrated moving average (ARIMA) model that was trained with the monthly incidence of PTB in China from January 2005 to December 2019. The interventional model was established using an ARIMA model with a continuing intervention function that was trained with the monthly PTB incidence in China from January 2020 to December 2020.ResultsStarting with the assumption that no COVID-19 outbreak had occurred in China, PTB incidence was predicted, and then the actual incidence was compared with the predicted incidence. A remarkable overall decline in PTB incidence from January 2020 to December 2020 was observed, which was likely due to the potential influence of intervention policies for COVID-19. If the same intervention strategy is applied for the next 2 years, the monthly PTB incidence would reduce on average by about 1.03 per 100,000 people each month compared with the incidence predicted by the non-interventional model. The annual incidence estimated 59.15 under regular intervention per 100,000 in 2021, and the value would decline to 50.65 with strict interventions.ConclusionsOur models quantified the potential knock-on effect on PTB incidence of the intervention strategy used to control the transmission of COVID-19 in China. Combined with the feasibility of the strategies, these results suggested that continuous regular interventions would play important roles in the future prevention and control of PTB.
Project description:BackgroundRoutine services for tuberculosis (TB) are being disrupted by stringent lockdowns against the novel SARS-CoV-2 virus. We sought to estimate the potential long-term epidemiological impact of such disruptions on TB burden in high-burden countries, and how this negative impact could be mitigated.MethodsWe adapted mathematical models of TB transmission in three high-burden countries (India, Kenya and Ukraine) to incorporate lockdown-associated disruptions in the TB care cascade. The anticipated level of disruption reflected consensus from a rapid expert consultation. We modelled the impact of these disruptions on TB incidence and mortality over the next five years, and also considered potential interventions to curtail this impact.FindingsEven temporary disruptions can cause long-term increases in TB incidence and mortality. If lockdown-related disruptions cause a temporary 50% reduction in TB transmission, we estimated that a 3-month suspension of TB services, followed by 10 months to restore to normal, would cause, over the next 5 years, an additional 1⋅19 million TB cases (Crl 1⋅06-1⋅33) and 361,000 TB deaths (CrI 333-394 thousand) in India, 24,700 (16,100-44,700) TB cases and 12,500 deaths (8.8-17.8 thousand) in Kenya, and 4,350 (826-6,540) cases and 1,340 deaths (815-1,980) in Ukraine. The principal driver of these adverse impacts is the accumulation of undetected TB during a lockdown. We demonstrate how long term increases in TB burden could be averted in the short term through supplementary "catch-up" TB case detection and treatment, once restrictions are eased.InterpretationLockdown-related disruptions can cause long-lasting increases in TB burden, but these negative effects can be mitigated with rapid restoration of TB services, and targeted interventions that are implemented as soon as restrictions are lifted.FundingUSAID and Stop TB Partnership.
Project description:The latest version of human coronavirus said to be COVID-19 came out as a sudden pandemic disease within human population and in the absence of vaccination and proper treatment till date, it daunting threats heavily to human lives, infecting more than 12, 11, 214 people and death more than 67, 666 people in 208 countries across the globe as on April 06, 2020, which is highly alarming. When no treatment or vaccine is available till date and to avoid COVID-19 to be transmitted in the community, social distancing is the only way to prevent the disease, which is well taken into account in our novel epidemic models as a special compartment, that is, home isolation. Based on the transmitting behavior of COVID-19 in the human population, we develop three quarantine models of this pandemic taking into account the compartments: susceptible population, immigrant population, home isolation population, infectious population, hospital quarantine population, and recovered population. Local and global asymptotic stability is proved for all the three models. Extensive numerical simulations are performed to establish the analytical results with suitable examples. Our research reveals that home isolation and quarantine to hospitals are the two pivot force-control policies under the present situation when no treatment is available for this pandemic.
Project description:The coronavirus pandemic (COVID-19) is associated with secondary bacterial and fungal infections globally. In India, inappropriate use of glucocorticoids, high prevalence of diabetes mellitus and a conducive environment for fungal growth are considered as the main factors for increased incidence of COVID-19 associated mucormycosis (CAM). Few cases of CAM without steroid abuse and normal blood glucose levels were also reported during the pandemic. This study was designed to explore whether altered immune responses due to severe COVID-19 infection predisposes towards development of mucormycosis. The global transcriptome profiling of monocytes and granulocytic cells derived from CAM, Mucormycosis, COVID-19 and healthy control groups were performed to identify the differentially expressed genes (DEGs) involved in dysregulated host immune response towards respective diseased and healthy conditions.