The National Collaborating Centres (NCCs) for Public Health (NCCPH) were established in 2005 as part of the federal government's commitment to renew and strengthen public health following the severe acute respiratory syndrome (SARS) epidemic. They were set up to support knowledge translation for more timely use of scientific research and other knowledges in public health practice, programs and policies in Canada. Six centres comprise the NCCPH, including the National Collaborating Centre for Infectious Diseases (NCCID). The NCCID works with public health practitioners to find, understand and use research and evidence on infectious diseases and related determinants of health. The NCCID has a mandate to forge connections between those who generate and those who use infectious diseases knowledge. As the first article in a series on the NCCPH, we describe our role in knowledge brokering and the numerous methods and products that we have developed. In addition, we illustrate how NCCID has been able to work with public health to generate and share knowledge during the coronavirus disease 2019 (COVID-19) pandemic.
Antioquia Department is the state with the highest burden of tuberculosis (TB) in Colombia. Our aim was to determine the risk factors associated with unsuccessful TB treatment in HIV-seropositive and homeless persons, compared with non–HIV-infected and non-homeless persons with TB. We conducted a retrospective cohort study using observational, routinely collected health data from all drug-susceptible TB cases in homeless and/or HIV-seropositive individuals in Antioquia from 2014 to 2016. Unsuccessful TB treatment was defined as individuals having been lost to follow-up, having died, or treatment failure occurrence during the study period. Successful treatment was defined as cure of TB or treatment completion according to the WHO definitions. We identified 544 homeless persons with TB (432 HIV− and 112 HIV+), 835 HIV+ persons with TB and non-homeless, and 5,086 HIV−/non-homeless people with TB. Unsuccessful treatment rates were 19.3% in HIV−/non-homeless persons, 37.4% in non-homeless HIV+ patients, 61.5% in homeless HIV− patients, and 70.3% in homeless HIV+ patients; all rates fall below End TB strategy targets. More than 50% of homeless patients were lost to follow-up. Risk factors associated with unsuccessful treatment were HIV seropositivity, homelessness, male gender, age ≥ 25 years, noncontributory-type health insurance, TB diagnosis made during hospitalization, and previous treatment for TB. These results highlight the challenge of treating TB in the homeless population. These findings should put an onus on TB programs, governments, clinicians, and others involved in the collaborative care of TB patients to pursue innovative strategies to improve treatment success in this population.
Although Canada has one of the lowest tuberculosis incidence rates in the world, certain groups are disproportionately affected, including foreign born people from high incidence countries. The Winnipeg Regional Health Authority has initiated a process to decentralize latent tuberculosis infection (LTBI) management at primary care clinics in Winnipeg. One of these clinics is BridgeCare Clinic which provides services to government-assisted refugees. The present study describes the BridgeCare Clinic LTBI program and reviews program outcomes from January 2015 to October 2016. Refugees at BridgeCare Clinic receive comprehensive care, including LTBI screening and treatment. The LTBI program is managed by physicians, nurse practitioners, and primary care nurses under a patient-centered model of care. An accessible interpretation service, education to clients, and laboratory sampling at the clinic with free IGRA testing are important components of the program. Anonymized data on client outcomes were statistically analyzed and qualitative interviews were conducted with senior staff. During the study period, 274 IGRA tests were ordered with 158 negative results (57.7%) and 101 positive results (36.9%). Of 45 clients eligible (from January to December 2015) for LTBI treatment, 11 (24.4%) declined to receive treatment and 34 (75.6%) started treatment. Twenty-seven (79.4%) clients completed treatment, 3 (8.8%) clients moved out of province, and 4 (11.8%) did not complete treatment. The most recent World Health Organization strategy for tuberculosis control calls for integrated, patient-centered care and prevention. Aligned with these WHO recommendations, our experience suggests that LTBI care and treatment can be delivered effectively in a primary care setting using an integrated patient-centered approach.
ObjectivePost-acute COVID-19 (or 'long COVID') manifests as a wide range of long-lasting symptoms affecting multiple organ systems. We are developing criteria for identifying long COVID cases using administrative, clinical, survey and other data from Manitoba, Canada, with the ultimate goal of examining long COVID prevalence, risk factors, prognosis and recovery. ApproachGiven the lack of an accepted clinical definition and resulting lack of diagnostic codes, we are adopting several different creative and complementary strategies to identify long COVID cases. We are examining administrative and clinical data sources (laboratory data, physician claims, drug prescriptions, and electronic medical records) for information on positive COVID tests, common symptoms and complaints, and treatment provided. To identify people with long COVID who may not have sought healthcare, we are collecting survey data from a convenience community sample (members of a medical health fitness facility) and mining data on long COVID symptoms from Twitter. ResultsThe combination of approaches we have adopted and the expanding scientific literature on long COVID are contributing to a more comprehensive understanding of the impacts of long COVID in Manitoba. Through preliminary work on the laboratory data (positive COVID tests March 2020-June 2021), we have developed and characterized a COVID-positive cohort (n=47,515). Work is now underway to develop an algorithm for long COVID using symptoms from free text in electronic medical records, ICD-9 codes, and changes in health-seeking behaviour (compared to the pre-positive COVID test period and a matched sample). This population data-driven approach will then allow us to examine how multiple underlying health conditions, COVID illness severity, COVID vaccination status, and various socio-demographic factors are related to risk of long COVID. ConclusionThis research is generating actionable information by identifying risk factors to support clinical diagnosis of long COVID, making it easier for clinicians to recognize this new illness and develop plans to manage it, and will inform healthcare system planning by quantifying the burden of long COVID at the population level.
