Background: Long COVID is a post-severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection syndrome characterised by not recovering for several weeks or months following the acute episode. The effectiveness of COVID-19 vaccines against long-term symptoms of COVID19 is not well understood. We determined whether vaccination was associated with reporting long-term symptoms post-SARS-CoV-2 infection by comparing, among individuals previously infected with SARS-CoV-2, those who were vaccinated to those who were not, in terms of self-reported long-term symptoms. Methods: We invited individuals who were PCR tested for SARS-CoV-2 infection at participating hospitals between March 2020-June 2021 to fill an online questionnaire that included baseline demographics, details of their acute episode and information about symptoms they were currently experiencing. Using binomial regression, we compared vaccinated individuals with those unvaccinated in terms of self-reported symptoms post-acute infection. Results: Of 951 previously infected individuals who filled the survey 637(67%) were vaccinated. The most commonly reported symptoms were; fatigue (22%), headache (20%), weakness (13%), and persistent muscle pain (10%). After adjusting for follow-up time and baseline symptoms, fully vaccinated (2 or more doses) individuals were less likely than unvaccinated individuals to report any of these symptoms by 64%, 54%, 57%, and 68% respectively, (Risk ratios 0.36, 0.46, 0.43, 0.32, p<0.04 in the listed sequence). Conclusions: Vaccination with at least two doses of COVID-19 vaccine was associated with a substantial decrease in reporting the most common post-acute COVID19 symptoms. Our results suggest that, in addition to reducing the risk of acute illness, COVID-19 vaccination may have a protective effect against long COVID.

The effectiveness of Coronavirus disease 2019 (COVID-19) vaccines against the long-term COVID-19 symptoms expressed by a substantial proportion of patients is not well understood. We determined whether vaccination with the BNT162b2 mRNA vaccine was associated with incidence of reporting long-term symptoms post-SARS-CoV-2 infection. We invited individuals PCR-tested for SARS-CoV-2 infection at participating hospitals between March 2020 and November 2021 to fill an online questionnaire that included information about demographics, acute COVID-19 episode and symptoms they were currently experiencing. Using binomial regression, we compared vaccinated individuals with those unvaccinated and those uninfected, in terms of post-acute self-reported symptoms. Of the 951 infected, 637(67%) were vaccinated. In the study population, the most prevalent symptoms were: fatigue (22%), headache (20%), weakness of limbs (13%), and persistent muscle pain (10%). After adjusting for age, time from beginning of symptoms to responding to the survey, and baseline symptoms, those who received two vaccine doses were less likely than unvaccinated individuals to report any of these symptoms (fatigue, headache, weakness of limbs, persistent muscle pain) by 62%, 50%, 62%, and 66% respectively, (Risk ratios 0.38, 0.50, 0.38, 0.34, p < 0.04 in the listed sequence). Compared to the 2447 included individuals who never reported SARS-CoV-2 infection, double-vaccinated participants were no more likely to report any of the mentioned symptoms. Vaccination with 2+ doses of BNT162b2 was associated with a reduced risk of reporting most of the common post-acute COVID-19 symptoms. Our results suggest that BNT162b2 vaccination may have a protective effect against longer term COVID-19 symptoms.

ObjectivesAddressing the barriers to early breast and cervical cancer diagnosis in low and middle-income countries (LMICs) requires a sound understanding and accurate assessment of diagnostic timeliness. This review aimed to map the current evidence on the time to breast and cervical cancer diagnosis and associated factors in LMICs.DesignScoping review.SourcesMEDLINE (via PubMed), Cochrane Library, Scopus and CINAHL.Eligibility criteriaStudies describing the time to diagnosis and associated factors in the context of breast and cervical cancer in LMICs published from 1 January 2010 to 20 May 2021.Study selection and data synthesisTwo reviewers independently screened all abstracts and full texts using predefined inclusion criteria. The review was reported in accordance with the Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews. Evidence was narratively synthesised using predefined themes.ResultsTwenty-six studies conducted across 24 LMICs were included in the review, most (24/26) of which focused on breast cancer. Studies varied considerably in their conceptualisation and assessment of diagnostic time, events, intervals and delays, with a minority of the studies reporting the use of validated methods and tools. Patient-related intervals and delays were more frequently evaluated and reported than provider-related and health system-related intervals and delays. Across studies, there were variations in the estimated lengths of the appraisal, help-seeking, patient and diagnostic intervals for both cancers and the factors associated with them.ConclusionsDespite the significant burden of breast and cervical cancer in LMICs, there is limited information on the timeliness of diagnosis of these cancers. Major limitations included variations in conceptualisation and assessment of diagnostic events and intervals. These underscore the need for the use of validated and standardised tools, to improve accuracy and translation of findings to better inform interventions for addressing diagnostic delays in LMICs.

The International Severe Acute Respiratory and Emerging Infection Consortium (ISARIC) COVID-19 dataset is one of the largest international databases of prospectively collected clinical data on people hospitalized with COVID-19. This dataset was compiled during the COVID-19 pandemic by a network of hospitals that collect data using the ISARIC-World Health Organization Clinical Characterization Protocol and data tools. The database includes data from more than 705,000 patients, collected in more than 60 countries and 1,500 centres worldwide. Patient data are available from acute hospital admissions with COVID-19 and outpatient follow-ups. The data include signs and symptoms, pre-existing comorbidities, vital signs, chronic and acute treatments, complications, dates of hospitalization and discharge, mortality, viral strains, vaccination status, and other data. Here, we present the dataset characteristics, explain its architecture and how to gain access, and provide tools to facilitate its use.

Background Antimicrobial resistance is currently a recognized global health problem stemming from poor antibiotic stewardship by health workers and inappropriate antimicrobial use by patients. Data showing the extent of poor antimicrobial stewardship in low- and middle-income countries are scanty though high incidences of antimicrobial resistance are increasingly reported in many settings across the globe. The objective of the present study was, therefore, to evaluate prescriptions for antimicrobials in East Africa. Methods A comprehensive literature search strategy that includes text words and medical subject headings was developed and applied to predefined electronic databases. Two authors independently screened the titles and abstracts of the outputs of the literature search. Full texts were then independently reviewed by the first and the second authors. Eligible studies were formally assessed for quality and risk of bias using a scoring tool. Extracted data from included studies were combined in a meta-analysis where appropriate and presented using forest plots and tables or in a narrative text. Where data were available, subgroup analyses were performed. Results A total of 4284 articles were retrieved, but only 26 articles were included in the review. The majority of the included studies (30.8%) were retrieved from Ethiopia, followed by Sudan, Kenya, and Tanzania each contributing 19.2% of the included studies. The overall proportion of encounters with antimicrobials reported by the included studies was 57% CI [42–73%]. Ethiopia had an overall patient encounter with antimicrobials of 63% [50–76%] followed by Sudan with an overall encounter with antimicrobials of 62% CI [34–85%]. Included studies from Kenya reported an overall encounter with antimicrobials of 54% CI [15–90%], whereas included studies from Tanzania reported an overall patient encounter with antimicrobials of 40% CI [21–60%]. Conclusion Prescription patterns demonstrated in this review significantly deviate from WHO recommendations suggesting inappropriate antimicrobial use in the East African countries. Further studies have to be pursued to generate more information on antimicrobial use in this region.