Project description:The initial cluster of severe pneumonia cases that triggered the COVID-19 epidemic was identified in Wuhan, China in December 2019. While early cases of the disease were linked to a wet market, human-to-human transmission has driven the rapid spread of the virus throughout China. The Chinese government has implemented containment strategies of city-wide lockdowns, screening at airports and train stations, and isolation of suspected patients; however, the cumulative case count keeps growing every day. The ongoing outbreak presents a challenge for modelers, as limited data are available on the early growth trajectory, and the epidemiological characteristics of the novel coronavirus are yet to be fully elucidated. We use phenomenological models that have been validated during previous outbreaks to generate and assess short-term forecasts of the cumulative number of confirmed reported cases in Hubei province, the epicenter of the epidemic, and for the overall trajectory in China, excluding the province of Hubei. We collect daily reported cumulative confirmed cases for the 2019-nCoV outbreak for each Chinese province from the National Health Commission of China. Here, we provide 5, 10, and 15 day forecasts for five consecutive days, February 5th through February 9th, with quantified uncertainty based on a generalized logistic growth model, the Richards growth model, and a sub-epidemic wave model. Our most recent forecasts reported here, based on data up until February 9, 2020, largely agree across the three models presented and suggest an average range of 7409-7496 additional confirmed cases in Hubei and 1128-1929 additional cases in other provinces within the next five days. Models also predict an average total cumulative case count between 37,415 and 38,028 in Hubei and 11,588-13,499 in other provinces by February 24, 2020. Mean estimates and uncertainty bounds for both Hubei and other provinces have remained relatively stable in the last three reporting dates (February 7th - 9th). We also observe that each of the models predicts that the epidemic has reached saturation in both Hubei and other provinces. Our findings suggest that the containment strategies implemented in China are successfully reducing transmission and that the epidemic growth has slowed in recent days.

Project description:BACKGROUND:Tuberculosis (TB) is the leading cause of death in South Africa. The burden of disease varies by age, with peaks in TB notification rates in the HIV-negative population at ages 0-5, 20-24, and 45-49 years. There is little variation between age groups in the rates in the HIV-positive population. The drivers of this age pattern remain unknown. METHODS:We developed an age-structured simulation model of Mycobacterium tuberculosis (Mtb) transmission in Cape Town, South Africa. We considered five states of TB progression: susceptible, infected (latent TB), active TB, treated TB, and treatment default. Latently infected individuals could be re-infected; a previous Mtb infection slowed progression to active disease. We further considered three states of HIV progression: HIV negative, HIV positive, on antiretroviral therapy. To parameterize the model, we analysed treatment outcomes from the Cape Town electronic TB register, social mixing patterns from a Cape Town community and used literature estimates for other parameters. To investigate the main drivers behind the age patterns, we conducted sensitivity analyses on all parameters related to the age structure. RESULTS:The model replicated the age patterns in HIV-negative TB notification rates of Cape Town in 2009. Simulated TB notification rate in HIV-negative patients was 1000/100,000 person-years (pyrs) in children aged <5 years and decreased to 51/100,000 in children 5-15 years. The peak in early adulthood occurred at 25-29 years (463/100,000 pyrs). After a subsequent decline, simulated TB notification rates gradually increased from the age of 30 years. Sensitivity analyses showed that the dip after the early adult peak was due to the protective effect of latent TB and that retreatment TB was mainly responsible for the rise in TB notification rates from the age of 30 years. CONCLUSION:The protective effect of a first latent infection on subsequent infections and the faster progression in previously treated patients are the key determinants of the age-structure of TB notification rates in Cape Town.

Project description:BackgroundAgainst a backdrop of declining tobacco use, e-cigarette markets are growing. The UK now has a higher percentage of e-cigarette users than any other European country. These developments have prompted fierce discussions in scientific, advocacy and policy communities about how best to respond. This article is one of the first to examine the role of evidence in these debates.MethodsWe analysed 121 submissions to two Scottish policy consultations on e-cigarettes (in 2014 and 2015) and undertook interviews with 26 key informants in 2015-2016, following up with a sub-set in 2019-2020. All data were thematically coded, and our analysis was informed by insights from policy studies and the sociology of science.ResultsFirst, we affirm previous research in suggesting that e-cigarettes appeared to have triggered a breakdown of old public health alliances. Second, we demonstrate that, amid concerns about research quality and quantity, actors are guided by normative outlooks (and/or economic interests) in their assessments of evidence. Third, we show that, despite describing e-cigarette debates as contentious and polarised, actors engaging in Scottish policy debates exhibit a spectrum of views, with most interviewees occupying an uncertain 'middle ground' that is responsive to new evidence. Fourth, we suggest that the perceived divisiveness of e-cigarette debates is attributed to recurrent media simplifications and tensions arising from the behaviours of some actors with settled positions working to promote particular policy responses (including by strategically enrolling supportive evidence). Fifth, we argue that the actions of these actors are potentially explained by the prospect that e-cigarettes could usher in a new tobacco 'policy paradigm'. Finally, we show how scientific authority is employed as a tool within these debates.ConclusionsE-cigarette debates are likely to reconcile only if a clear majority of participants in the uncertain 'middle ground' settle on a more fixed position. Our results suggest that many participants in Scottish e-cigarette debates occupy this 'middle ground' and express concerns that can be empirically assessed, implying evidence has the potential to play a more important role in settling e-cigarette debates than previous research suggests.

Dataset Information

5th Scientific Workshops and Debates of the Pulmonary Vascular Research Institute (PVRI) Cape Town, South Africa 7-10 February, 2012

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