ABSTRACT
Background Persons in Pakistan have suffered from various infectious diseases over the years, each impacted by various factors including climate change, seasonality, geopolitics, and resource availability. The COVID-19 pandemic is another complicating factor, with changes in the reported incidence of endemic infectious diseases and related syndromes under surveillance.Methods We assessed the monthly incidence of 8 important infectious diseases/syndromes: acute respiratory infection (ARI), viral hepatitis, malaria, pneumonia, diarrhea, typhoid fever, measles, and neonatal tetanus (NNT), before and after the onset of the COVID-19 pandemic. Administrative health data of monthly reported cases of these diseases/syndromes from all 5 provinces/regions of Pakistan for a 3-y interval (March 2018 – February 2021) were analyzed using an interrupted time series approach. Reported monthly incidence for each infectious disease agent or syndrome and COVID-19 were subjected to time series visualization. Spearman’s rank correlation coefficient between each infectious disease/syndrome and COVID-19 was calculated and median case numbers of each disease before and after the onset of the COVID-19 pandemic were compared using a Wilcoxon signed-rank test. Subsequently, a generalized linear negative binomial regression model was developed to determine the association between reported cases of each disease and COVID-19.Results In late February 2020, concurrent with the start of COVID-19, in all provinces, there were decreases in the reported incidence of the following diseases: ARI, pneumonia, hepatitis, diarrhea, typhoid, and measles. In contrast, the incidence of COVID was negatively associated with the reported incidence of NNT only in Punjab and Sindh, but not in Khyber Pakhtunkhwa (KPK), Balochistan, or Azad Jammu & Kashmir (AJK) & Gilgit Baltistan (GB). Similarly, COVID-19 was associated with a lowered incidence of malaria in Punjab, Sindh, and AJK & GB, but not in KPK and Balochistan.Conclusions COVID-19 was associated with a decreased reported incidence of most infectious diseases/syndromes studied in most provinces of Pakistan. However, exceptions included NNT in KPK, Balochistan and AJK & GB, and malaria in KPK and Balochistan. This general trend was attributed to a combination of resource diversion, misdiagnosis, misclassification, misinformation, and seasonal patterns of each disease.
Subject(s)
COVID-19ABSTRACT
Background: Pneumonia from SARS-CoV-2 is difficult to distinguish from other viral and bacterial etiologies. Broad-spectrum antimicrobials are frequently prescribed to patients hospitalized with COVID-19 which potentially acts as a catalyst for the development of antimicrobial resistance (AMR). ObjectivesWe conducted a systematic review and meta-analysis during the first 18 months of the pandemic to quantify the prevalence and types of resistant co-infecting organisms in patients with COVID-19 and explore differences across hospital and geographic settings.MethodsWe searched MEDLINE, Embase, Web of Science (BioSIS), and Scopus from November 1, 2019 to May 28, 2021 to identify relevant articles pertaining to resistant co-infections in patients with laboratory confirmed SARS-CoV-2. Patient- and study-level analyses were conducted. We calculated pooled prevalence estimates of co-infection with resistant bacterial or fungal organisms using random effects models. Stratified meta-analysis by hospital and geographic setting was also performed to elucidate any differences. ResultsOf 1331 articles identified, 38 met inclusion criteria. A total of 1959 unique isolates were identified with 29% (569) resistant organisms identified. Co-infection with resistant bacterial or fungal organisms ranged from 0.2 to 100% among included studies. Pooled prevalence of co-infection with resistant bacterial and fungal organisms was 24% (95% CI: 8-40%; n=25 studies: I 2 =99%) and 0.3% (95% CI: 0.1-0.6%; n=8 studies: I 2 =78%), respectively. Among multi-drug resistant organisms, methicillin-resistant Staphylococcus aureus, carbapenem-resistant Acinetobacter baumannii, Klebsiella pneumoniae, Pseudomonas aeruginosa and Candida auris were most commonly reported. Stratified analyses found higher proportions of AMR outside of Europe and in ICU settings, though these results were not statistically significant. Patient-level analysis demonstrated >50% (n=58) mortality, whereby all but 6 patients were infected with a resistant organism. ConclusionsDuring the first 18 months of the pandemic, AMR was moderately prevalent in COVID-19 patients and varied by hospital and geography although there was substantial heterogeneity. Given the variation in patient populations within these studies, clinical settings, practice patterns, and definitions of AMR, further research is warranted to quantify AMR in COVID-19 patients to improve surveillance programs, infection prevention and control practices and antimicrobial stewardship programs globally.
Subject(s)
COVID-19 , Klebsiella InfectionsABSTRACT
COVID-19 has affected all countries. Its containment represents a unique challenge for India due to a large population (>1.38 billion) across a wide range of population densities. Assessment of the COVID-19 disease burden is required to put the disease impact into context and support future pandemic policy development. Here, we present the national-level burden of COVID-19 in India in 2020 that accounts for differences across urban and rural regions and across age groups. Disability-adjusted life years (DALY) due to COVID-19 were estimated in the Indian population in 2020, comprised of years of life lost (YLL) and years lived with disability (YLD). Scenario analyses were conducted to account for excess deaths not recorded in the official data and for reported COVID-19 deaths. The direct impact of COVID-19 in 2020 in India was responsible for 14,106,060 (95% uncertainty interval [UI] 14,030,129–14,213,231) DALYs, consisting of 99.2% (95% UI 98.47–99.64%) YLLs and 0.80% (95% UI 0.36–1.53) YLDs. DALYs were higher in urban (56%; 95% UI 56–57%) than rural areas (44%; 95% UI 43.4–43.6) and in males (64%) than females (36%). In absolute terms, the highest DALYs occurred in the 51–60-year-old age group (28%) but the highest DALYs per 100,000 persons were estimated for the 71-80 year old age group (5,481; 95% UI 5,464–5,500 years). There were 4,823,791 (95% UI 4,760,908–4,924,307) DALYs after considering reported COVID-19 deaths only. The DALY estimations have direct and immediate implications not only for public policy in India, but also internationally given that India represents one sixth of the world’s population.