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1.
BMJ INNOVATIONS ; 8(2):111-116, 2022.
Article in English | Web of Science | ID: covidwho-1938028
2.
BJOG-AN INTERNATIONAL JOURNAL OF OBSTETRICS AND GYNAECOLOGY ; 129:21-22, 2022.
Article in English | Web of Science | ID: covidwho-1905002
3.
R Soc Open Sci ; 8(9): 202218, 2021 Sep.
Article in English | MEDLINE | ID: covidwho-1429383

ABSTRACT

Drawing on risk methods from volcano crises, we developed a rapid COVID-19 infection model for the partial return of pupils to primary schools in England in June and July 2020, and a full return in September 2020. The model handles uncertainties in key parameters, using a stochastic re-sampling technique, allowing us to evaluate infection levels as a function of COVID-19 prevalence and projected pupil and staff headcounts. Assuming average national adult prevalence, for the first scenario (as at 1 June 2020) we found that between 178 and 924 [90% CI] schools would have at least one infected individual, out of 16 769 primary schools in total. For the second return (July), our estimate ranged between 336 (2%) and 1873 (11%) infected schools. For a full return in September 2020, our projected range was 661 (4%) to 3310 (20%) infected schools, assuming the same prevalence as for 5 June. If national prevalence fell to one-quarter of that, the projected September range would decrease to between 381 (2%) and 900 (5%) schools but would increase to between 2131 (13%) and 9743 (58%) schools if prevalence increased to 4× June level. When regional variations in prevalence and school size distribution were included in the model, a slight decrease in the projected number of infected schools was indicated, but uncertainty on estimates increased markedly. The latter model variant indicated that 82% of infected schools would be in areas where prevalence exceeded the national average and the probability of multiple infected persons in a school would be higher in such areas. Post hoc, our model projections for 1 September 2020 were seen to have been realistic and reasonable (in terms of related uncertainties) when data on schools' infections were released by official agencies following the start of the 2020/2021 academic year.

4.
British Journal of Surgery ; 108:34-34, 2021.
Article in English | Web of Science | ID: covidwho-1254510
5.
R Soc Open Sci ; 8(1): 201566, 2021 Jan.
Article in English | MEDLINE | ID: covidwho-1093628

ABSTRACT

Personal contacts drive COVID-19 infections. After being closed (23 March 2020) UK primary schools partially re-opened on 1 June 2020 with social distancing and new risk mitigation strategies. We conducted a structured expert elicitation of teachers to quantify primary school contact patterns and how contact rates changed upon re-opening with risk mitigation measures in place. These rates, with uncertainties, were determined using a performance-based algorithm. We report mean number of contacts per day for four cohorts within schools, with associated 90% confidence ranges. Prior to lockdown, younger children (Reception and Year 1) made 15 contacts per day [range 8.35] within school, older children (Year 6) 18 contacts [range 5.55], teaching staff 25 contacts [range 4.55] and non-classroom staff 11 contacts [range 2.27]. After re-opening, the mean number of contacts was reduced by 53% for young children, 62% for older children, 60% for classroom staff and 64% for other staff. Contacts between teaching and non-teaching staff reduced by 80%. The distributions of contacts per person are asymmetric with heavy tail reflecting a few individuals with high contact numbers. Questions on risk mitigation and supplementary structured interviews elucidated how new measures reduced daily contacts in-school and contribute to infection risk reduction.

6.
S Afr Med J ; 110(9): 835-836, 2020 08 12.
Article in English | MEDLINE | ID: covidwho-745266

ABSTRACT

The stated objective of the COVID-19 lockdown was to allow time to prepare healthcare facilities. Preparation must include administrative and environmental measures, which when combined with personal protective equipment, minimise the risk of the spread of infection to patients and healthcare workers (HCWs) in facilities, allowing HCWs to safely provide essential services during the pandemic and limit the indirect effects of COVID-19 caused by healthcare disruption. We present our model for facility preparation based on colour-coded zones, social distancing, hand hygiene, rapid triage and separate management of symptomatic patients, and attention to infection transmission prevention between HCWs in communal staff areas. This model specifically addresses the challenges in preparing a facility for COVID-19 in a low-resource setting and in rural areas. In addition, we include links to resources to allow workers in low-resource settings to prepare their facilities adequately.


Subject(s)
Coronavirus Infections/epidemiology , Delivery of Health Care/organization & administration , Health Facilities , Health Personnel , Pneumonia, Viral/epidemiology , Ambulatory Care Facilities , Betacoronavirus , COVID-19 , Capacity Building , Coronavirus Infections/prevention & control , Coronavirus Infections/transmission , Disinfection , Environment Design , Hand Disinfection , Hospitals , Humans , Infection Control , Mobile Health Units , Pandemics/prevention & control , Personal Protective Equipment/supply & distribution , Pneumonia, Viral/prevention & control , Pneumonia, Viral/transmission , SARS-CoV-2 , South Africa/epidemiology , Ventilators, Mechanical/supply & distribution
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