Non parametric approaches to understanding disease transmissions dynamics in the context of policy information

在政策信息背景下理解疾病传播动态的非参数方法

• 批准号: 2446052
• 金额: --
• 依托单位: Imperial College London
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2020
• 资助国家: 英国
• 起止时间: 2020 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-2446052
• 关键词: Non; parametric; approaches; understanding; disease

In my DPhil thesis "non parametric approaches to understanding disease transmissions dynamics in the context of policy information", supervised by Dr. Oliver Ratmann, I am aiming to develop epidemiological models to better understand the spread of dangerous infective diseases.In particular, we will focus on HIV in southcentral Uganda, where HIV prevalence ranges up to 40% in some communities. The introduction of the Universal Test and Treatment rollout in the last years lead to improvements of the treatment of the disease, however prevalence has decreased modestly.Simultaneously, increases in HIV drug resistance have been observed, and the COVID-19 pandemic has caused severe disruption in the healthcare facilities. In this context, the large, population-level, prospective study RCSS is providing data to document transmissions and viremia over time, as well as providing phylogenetic data to analyse. One of our main goals will be to develop Bayesian non-parametric models to compare HIV viremia and drug resistance before and after the COVID-19 epidemic, in order to assess the effectiveness of policies targeted at epidemic control. Further, we aim to quantify the disruption caused by the COVID-19 pandemic on risk of HIV transmission, as well as on healthcare facilities, treatment and prevention.The study will be significant in understanding whether the UNAIDS goals for the 'end AIDS by 2030' - fewer than 200,000 new infections among adults- are feasible with the current policies.Further, it will provide insight on the evolution of HIV drug resistance. Although the study is limited to Ugandan communities, we expect the results to be applicable in other African countries.The main project is still in its early stages, as I spent the latest half of my first year on another epidemiological problem.In particular, I took part to a multi-disciplinary study aiming to understand the observed wide changes of COVID-19 in-hospital fatality rates in Brazil.We used public available data from various Brazilian institutes to assess which factor was more strongly associated with higher fatality: differences among cities, dates of emergence of the Gamma variant, or increases in hospital resource demand.The various effect were hard to disentangle, but we used a Bayesian multistrain model to estimate the variant dynamics to, in turn, estimate the proportion of hospitalisations with a given variant. We found that Gamma's consequences on fatality were mainly mediated through resurgence in COVID-19 transmission rather than an increase in disease severity attributable to Gamma. This meant that locations with effective non-pharmaceutical intervention and more equipped healthcare systems did not observe as dramatic consequences as other cities.We hope that the above findings and our conclusion that a significant proportion of hospitalisations could have been saved will soon be published, as we just submitted a manuscript.In my HIV project, I will use the knowledge and experience gained in the last month to better model and quantify the different factors coming into play.The study of epidemic outbreaks and policies to tackle infectious diseases makes the project fall within the EPSRC Global uncertainties research area.

在我的DPhil论文《在政策信息背景下了解疾病传播动态的非参数方法》中，我的目标是开发流行病学模型，以更好地了解危险传染病的传播。特别是，我们将重点关注乌干达中南部的艾滋病毒，那里的艾滋病毒流行率在某些社区高达40%。去年推出的普遍检测和治疗措施改善了这种疾病的治疗，但患病率略有下降。同时，观察到艾滋病毒抗药性的增加，以及新冠肺炎大流行对医疗设施造成了严重破坏。在此背景下，人口层面的大型前瞻性研究RCS正在提供数据，以记录随时间推移的传播和病毒血症，并提供系统发育数据进行分析。我们的主要目标之一将是开发贝叶斯非参数模型，比较新冠肺炎疫情前后艾滋病毒病毒血症和耐药性，以评估针对疫情控制的政策的有效性。此外，我们的目标是量化新冠肺炎大流行对艾滋病毒传播风险以及对医疗设施、治疗和预防的破坏。这项研究将对理解联合国艾滋病规划署提出的到2030年结束艾滋病的目标--成人新感染病例不到20万人--在当前政策下是否可行。此外，它将为艾滋病毒耐药性的演变提供洞察。虽然这项研究仅限于乌干达社区，但我们预计结果也适用于其他非洲国家。主要项目仍处于早期阶段，因为我第一年的最后一半时间是在另一个流行病学问题上度过的。特别是，我参加了一项多学科研究，旨在了解观察到的巴西新冠肺炎住院死亡率的广泛变化。我们使用来自巴西各研究所的公开可用数据，来评估哪个因素与更高的死亡率更密切相关：城市之间的差异，伽玛病毒变异出现的日期，还是医院资源需求的增加。各种影响很难区分。但我们使用贝叶斯多应变模型来估计变异动态，进而估计有给定变异的住院比例。我们发现，伽玛对死亡率的影响主要是通过新冠肺炎传播的死灰复燃来调节的，而不是由于伽玛导致的疾病严重性的增加。这意味着拥有有效的非药物干预和装备更好的医疗系统的地点没有像其他城市那样观察到严重的后果。我们希望上述发现和我们的结论很快就会发表，因为我们刚刚提交了一篇手稿。在我的艾滋病毒项目中，我将使用上个月获得的知识和经验来更好地对影响因素进行建模和量化。对流行病爆发和应对传染病的政策的研究使该项目属于EPSRC全球不确定性研究范围。

项目成果

Spatial and temporal fluctuations in COVID-19 fatality rates in Brazilian hospitals.

• DOI: 10.1038/s41591-022-01807-1
• 发表时间: 2022-07
• 期刊: NATURE MEDICINE
• 影响因子: 82.9
• 作者: Brizzi, Andrea;Whittaker, Charles;Servo, Luciana M. S.;Hawryluk, Iwona;Prete Jr, Carlos A.;de Souza, William M.;Aguiar, Renato S.;Araujo, Leonardo J. T.;Bastos, Leonardo S.;Blenkinsop, Alexandra;Buss, Lewis F.;Candido, Darlan;Castro, Marcia C.;Costa, Silvia F.;Croda, Julio;de Souza Santos, Andreza Aruska;Dye, Christopher;Flaxman, Seth;Fonseca, Paula L. C.;Geddes, Victor E. V.;Gutierrez, Bernardo;Lemey, Philippe;Levin, Anna S.;Mellan, Thomas;Bonfim, Diego M.;Miscouridou, Xenia;Mishra, Swapnil;Monod, Melodie;Moreira, Filipe R. R.;Nelson, Bruce;Pereira, Rafael H. M.;Ranzani, Otavio;Schnekenberg, Ricardo P.;Semenova, Elizaveta;Sonnabend, Raphael;Souza, Renan P.;Xi, Xiaoyue;Sabino, Ester C.;Faria, Nuno R.;Bhatt, Samir;Ratmann, Oliver
• 通讯作者: Ratmann, Oliver

Refining Reproduction Number Estimates to Account for Unobserved Generations of Infection in Emerging Epidemics.

• DOI: 10.1093/cid/ciac138
• 发表时间: 2022-08-24
• 期刊: Clinical infectious diseases : an official publication of the Infectious Diseases Society of America