Background Since the end of January 2020, the coronavirus (COVID-19) pandemic has been responsible for a global health crisis. In England a number of non-pharmaceutical interventions have been introduced throughout the pandemic, including guidelines on healthcare attendance (for example, promoting remote consultations), increased handwashing and social distancing. These interventions are likely to have impacted the incidence of non–COVID-19 conditions as well as healthcare seeking behaviour. Syndromic Surveillance Systems offer the ability to monitor trends in healthcare usage over time. Methods This study describes the indirect impact of COVID-19 on healthcare utilisation using a range of syndromic indicators including eye conditions, mumps, fractures, herpes zoster and cardiac conditions. Data from the syndromic surveillance systems monitored by Public Health England were used to describe the number of contacts with NHS 111, general practitioner (GP) In Hours (GPIH) and Out-of-Hours (GPOOH), Ambulance and Emergency Department (ED) services over comparable periods before and during the pandemic. Results The peak pandemic period in 2020 (weeks 13–20), compared to the same period in 2019, displayed on average a 12% increase in NHS 111 calls, an 11% decrease in GPOOH consultations, and a 49% decrease in ED attendances. In the GP In Hours system, conjunctivitis consultations decreased by 64% and mumps consultations by 31%. There was a 49% reduction in attendance at EDs for fractures, and there was no longer any weekend increase in ED fracture attendances, with similar attendance patterns observed across each day of the week. There was a decrease in the number of ED attendances with diagnoses of myocardial ischaemia. Conclusion The COVID-19 pandemic drastically impacted healthcare utilisation for non-COVID-19 conditions, due to a combination of a probable decrease in incidence of certain conditions and changes in healthcare seeking behaviour. Syndromic surveillance has a valuable role in describing and understanding these trends.
African trypanosomiasis is a vector-borne neglected tropical disease caused by parasites of the Trypanosoma genus that are cyclically transmitted through the bite of an infected tsetse fly. Two forms of the disease are endemic to sub-Saharan Africa: Human African Trypanosomiasis, also known as sleeping sickness, and Animal African Trypanosomiasis, commonly known as nagana (Aksoy et al., 2014). Nagana, caused by Trypanosoma brucei, Trypanosoma vivax, and Trypanosoma congolense, is considered to be the main disease that limits the trade of livestock in sub-Saharan Africa and kills approximately 3 million cattle annually, with an estimated loss of US
Previous research has demonstrated an association between the detection of antibodies to SARS-CoV-2 following natural infection and protection from subsequent symptomatic SARS-CoV-2 infection. Lateral flow immunoassays (LFIAs) detecting anti-SARS-CoV-2 IgG are a cheap, readily deployed technology that has been used on a large scale in population screening programs, yet no studies have investigated whether LFIA results are associated with subsequent SARS-CoV-2 infection.
ObjectiveTo develop a tool predicting individualised treatment for gonorrhoea, enabling treatment with previously recommended antibiotics, to reduce use of last-line treatment ceftriaxone.DesignA modelling study.SettingEngland and Wales.ParticipantsIndividuals accessing sentinel health services.InterventionDeveloping an Excel model which uses participants’ demographic, behavioural and clinical characteristics to predict susceptibility to legacy antibiotics. Model parameters were calculated using data for 2015–2017 from the Gonococcal Resistance to Antimicrobials Surveillance Programme.Main outcome measuresEstimated number of doses of ceftriaxone saved, and number of people delayed effective treatment, by model use in clinical practice. Model outputs are the predicted risk of resistance to ciprofloxacin, azithromycin, penicillin and cefixime, in groups of individuals with different combinations of characteristics (gender, sexual orientation, number of recent sexual partners, age, ethnicity), and a treatment recommendation.ResultsBetween 2015 and 2017, 8013 isolates were collected: 64% from men who have sex with men, 18% from heterosexual men and 18% from women. Across participant subgroups, stratified by all predictors, resistance prevalence was high for ciprofloxacin (range: 11%–51%) and penicillin (range: 6%–33%). Resistance prevalence for azithromycin and cefixime ranged from 0% to 13% and for ceftriaxone it was 0%. Simulating model use, 88% of individuals could be given cefixime and 10% azithromycin, saving 97% of ceftriaxone doses, with 1% of individuals delayed effective treatment.ConclusionsUsing demographic and behavioural characteristics, we could not reliably identify a participant subset in which ciprofloxacin or penicillin would be effective. Cefixime resistance was almost universally low; however, substituting ceftriaxone for near-uniform treatment with cefixime risks re-emergence of resistance to cefixime and ceftriaxone. Several subgroups had low azithromycin resistance, but widespread azithromycin monotherapy risks resistance at population level. However, this dataset had limitations; further exploration of individual characteristics to predict resistance to a wider range of legacy antibiotics may still be appropriate.
Background: SARS-CoV-2 vaccine coverage remains incomplete, being only 15% in low income countries. Rapid point of care tests predicting SARS-CoV-2 infection susceptibility in the unvaccinated might assist in risk management and vaccine prioritisation. Methods: We conducted a prospective cohort study in 2,826 participants working in hospitals and Fire and Police services in England, UK, during the pandemic (ISRCTN5660922). Plasma taken at recruitment in June 2020 was tested using four lateral flow immunoassay (LFIA) devices and two laboratory immunoassays detecting antibodies against SARS-CoV-2 (UK Rapid Test Consortium's AbC-19TM Rapid Test, OrientGene COVID IgG/IgM Rapid Test Cassette, SureScreen COVID-19 Rapid Test Cassette, and Biomerica COVID-19 IgG/IgM Rapid Test; Roche N and EUROIMMUN S laboratory assays). We monitored participants for microbiologically-confirmed SARS-CoV-2 infection for 200 days. We estimated associations between test results at baseline and subsequent infection, using Poisson regression models adjusted for baseline demographic risk factors for SARS-CoV-2 exposure. Findings: Positive IgG results on each of the four LFIAs were associated with lower rates of subsequent infection: adjusted incidence rate ratios (aIRRs) 0.00 (95% confidence interval 0.00-0.01), 0.03 (0.02-0.05), 0.07 (0.05-0.10), and 0.09 (0.07-0.12) respectively. The protective association was strongest for AbC-19 and SureScreen. The aIRR for the laboratory Roche N antibody assay at the manufacturer-recommended threshold was similar to those of the two best performing LFIAs at 0.03 (0.01-0.10). Interpretation: Lateral flow devices measuring SARS-CoV-2 IgG predicted disease risk in unvaccinated individuals over 200 day follow-up. The association of some LFIAs with subsequent infection was similar to laboratory immunoassays.
ObjectiveIn September 2020, records of 15,861 SARS-CoV-2 cases failed to upload from the Second Generation Laboratory Surveillance System (SGSS) to the Contact Tracing Advisory Service (CTAS) tool, resulting in a delay in the contact tracing of these cases. This study used CTAS data to determine the impact of this delay on health outcomes: transmission events, hospitalisations, and mortality. Previously, a modelling study had suggested a substantial impact.DesignObservational studySettingEngland.PopulationIndividuals testing positive for SARS-CoV-2 and their reported contacts.Main outcome measuresSecondary attack rates (SARs), hospitalisations, and deaths amongst primary and secondary contacts were calculated, compared to all other concurrent, unaffected cases. SGSS records affected by the event were matched to CTAS records and successive contacts and cases were identified.ResultsThe initiation of contact tracing was delayed by 3 days on average in the primary cases in the delay group (6 days) compared to the control group (3 days). This was associated with lower completion of contact tracing of primary cases in the delay group: 80% (95%CI: 79-81%) in the delay group and 83% (95%CI: 83-84%) in the control group. There was some evidence to suggest an increase in transmission to non-household contacts amongst those affected by the delay. The SAR for non-household contacts was higher amongst secondary contacts in the delay group than the control group (delay group: 7.9%, 95%CI:6.4% to 9.2%; control group: 5.9%, 95%CI: 5.3% to 6.6%). There was no evidence of a difference between the delay and control groups in the odds of hospitalisation (crude odds ratio: 1.1 (95%CI: 0.9 to 1.2) or death (crude odds ratio: 0.7 (0.1 to 4.0)) amongst secondary contacts.ConclusionsThe delay in contact tracing had a limited impact on population health outcomes.Strengths and limitations of the studyShows empirical data on the health impact of an event leading to a delay in contact tracing so can test hypotheses generated by models of the potential impact of a delay in contact tracingEstimates the extent of further transmission and odds of increased mortality or hospitalisation in up to the third generation of cases affected by the eventThe event acts as a natural experiment to describe the possible impact of contact tracing, comparing a group affected by chance by delayed contact tracing to a control group who experienced no delayContact tracing was not completed for all individuals, so the study might not capture all affected contacts or transmissions
Background Flooding can cause long-term, significant impacts on mental health in affected populations. We explored help-seeking behaviour of households affected by flooding. Methods A cross-sectional analysis was conducted on National Study of Flooding and Health data on households flooded in England in winter 2013/14. Participants (Year 1: n = 2006; Year 2: n = 988; Year 3: n = 819) were asked if they sought help from health services and other sources. Logistic regression was conducted to calculate odds ratios (ORs) of help-seeking in flooded and disrupted participants compared to unaffected, adjusted for a priori confounders. Results The odds of seeking help from any source 1 year after flooding were greater for flooded participants [adjusted OR (aOR): 1.71, 95% confidence interval (CI): 1.19–1.45] and those disrupted by flooding (aOR: 1.92, 95% CI: 1.37–2.68) compared to unaffected participants. This continued in the second year (flooded: aOR 6.24, 95% CI: 3.18–13.34; disrupted: aOR: 2.22, 95% CI: 1.14–4.68), and help-seeking remained greater in flooded than unaffected participants in the third year. Flooded and disrupted participants were particularly likely to seek help from informal sources. Help-seeking was more prevalent amongst participants with mental health outcomes, but a notable proportion of individuals with any mental health outcome did not seek help (Year 1: 15.0%; Year 2: 33.3%; Year 3: 40.3%). Conclusions Flooding is associated with increased demand for formal and informal support, persisting for at least 3 years, and an unmet need for help amongst affected individuals. Our findings should be considered in flood response planning to reduce the long-term adverse health impacts of flooding.
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