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1.
2020.
Non-conventional in English | Homeland Security Digital Library | ID: grc-740941

ABSTRACT

From the Introduction: In this report, we draw on data from nationally representative population surveys to explore a subset of inequities, how they relate to wealth and the way in which they may drive variation in COVID-19 [coronavirus disease 2019] risk. Using a dynamical model of COVID-19 transmission, we illustrate the potential for these factors (using the examples of availability of handwashing facilities, healthcare accessibility and capacity to work from home), individually or in combination, to lead to substantial inequalities in health outcomes and significant excess COVID-19 mortality in the poorest and most disadvantaged populations. We then discuss the potential for COVID-19 and associated interventions to have considerable indirect effects that may further concentrate the impact of COVID-19 into the poorest and most marginalised groups.COVID-19 (Disease);Poor;World health;Health risk assessment

2.
2020.
Non-conventional in English | Homeland Security Digital Library | ID: grc-740921

ABSTRACT

From the Introduction: The course of the COVID-19 [coronavirus disease 2019] epidemic in Low- and Middle-Income Countries (LMICs) will be determined by the actions that countries take in the coming weeks and months. It is clear that actions taken to reduce the size of the epidemic, delay, or flatten its peak, could lead to substantial reductions in deaths if doing so allows more patients with severe conditions to benefit from supportive care in hospital. However, the impact of the COVID-19 epidemic and actions taken in response to it will have far reaching consequences - including on other diseases, poverty, food security and economic growth - and consideration of these will have a strong bearing on the range of responses that are taken. Here we aim to provide information on just one of these aspects - the potential impact of the COVID19 epidemic on three other major health priorities;specifically, Human Immunodeficiency Virus (HIV), Tuberculosis (TB) and malaria.COVID-19 (Disease);Epidemics;Malaria;HIV infections;Tuberculosis

3.
2020.
Non-conventional in English | Homeland Security Digital Library | ID: grc-740912

ABSTRACT

From the Introduction: Following the emergence of a novel coronavirus (SARS-CoV-2) and its spread outside of China, Italy was the first European country to be hit by COVID-19 [coronavirus disease 2019]. [...] In this report we analyse the incidence of death reported across the 20 Italian regions, and along with the observed relative changes in regional movement, assess how interventions have impacted the transmissibility of SARS-CoV-2. We provide estimates of the number of deaths averted by the implementation of the control measures, the expected proportion of population infected (as of 1st May 2020), and explore the potential impact that the relaxation of the current interventions could have on disease transmission in the future. Understanding what impact the relaxation of the currently implemented NPIs ('exit strategies') will have on transmission is critical in guiding policy decisions to manage the transmission of COVID-19 in the so-called 'Phase 2'.COVID-19 (Disease);Epidemics

4.
2020.
Non-conventional | Homeland Security Digital Library | ID: grc-740911

ABSTRACT

In questo rapporto analizziamo l'incidenza delle morti dovute a COVID-19 nelle 20 regioni italiane e, insieme ai cambiamenti relativi del movimento osservati a livello regionale, valutiamo come questi interventi possano aver influito sulla trasmissibilità di SARS-CoV-2. Forniamo stime del numero di decessi evitati con l'attuazione delle attuali misure di controllo, la percentuale di popolazione infetta prevista (al 1° maggio 2020), ed esploriamo il potenziale impatto che il rilassamento delle attuali misure potrebbe avere sulla trasmissione della malattia nel futuro.COVID-19 (Disease);Epidemiology;Public health surveillance

5.
2020.
Non-conventional in English | Homeland Security Digital Library | ID: grc-740910

ABSTRACT

From the Introduction: To tackle the COVID-19 [coronavirus disease 2019] epidemic, fundamental changes to the provision of health and social services have been instituted in England. As a result, the NHS [National Health Service] undertook an unprecedented rearrangement of their resources, with specific measures including the postponing of non-urgent elective procedures and video-triaging patients for referral to hospital services. [...] Perhaps largely as a result of the widespread implementation of non-pharmaceutical interventions in England (and elsewhere), the country has seen a steady reduction in the daily number of COVID-19 cases and deaths. However, national data show that the number of attendances to accident and emergency (ED) services (i.e. consultant-led, 24-hour services including resuscitation units) have decreased nationally by approximately 50% across all England regions. Moreover, concerns have emerged that attendances to such emergency services remain low, even as the COVID-19 cases have dropped. [...] In this report, we use administrative patient level clinical hospital records from two large London hospitals from Imperial College Healthcare NHS Trust to analyse trends in attendances to ED departments and emergency admissions pre- and post-implementation of lock-down policies in England.Hospitals--Emergency services;COVID-19 (Disease);Public health

6.
2020.
Non-conventional in English | Homeland Security Digital Library | ID: grc-740551

ABSTRACT

From the Summary: In response to the COVID-19 [coronavirus disease 2019] pandemic, countries have sought to control transmission of SARS-CoV-2 [severe acute respiratory syndrome coronavirus 2] by restricting population movement through social distancing interventions, reducing the number of contacts. Mobility data represent an important proxy measure of social distancing. Here, we develop a framework to infer the relationship between mobility and the key measure of population-level disease transmission, the reproduction number (R). The framework is applied to 53 countries with sustained SARS-CoV-2 transmission based on two distinct country-specific automated measures of human mobility, Apple and Google mobility data.COVID-19 (Disease);Epidemics;Infectious disease;Emerging infectious diseases;Communicable diseases

7.
2020.
Non-conventional in English | Homeland Security Digital Library | ID: grc-740304

ABSTRACT

From the Summary: The COVID-19 [coronavirus disease 2019] pandemic is likely to severely interrupt health systems in Sub-Saharan Africa (SSA) over the coming weeks and months. Approximately 90% of malaria deaths occur in this region of the world, with an estimated 380,000 deaths from malaria in 2018. Much of the gain made in malaria control over the last decade has been due to the distribution of long-lasting insecticide treated nets (LLINs). Many SSA countries planned to distribute these in 2020. We used COVID-19 and malaria transmission models to understand the likely impact that disruption to these distributions, alongside other core health services, could have on the malaria burden. Results indicate that if all malaria-control activities are highly disrupted then the malaria burden in 2020 could more than double that in the previous year, resulting in large malaria epidemics across the region. These will depend on the course of the COVID-19 epidemic and how it interrupts local health system. Our results also demonstrate that it is essential to prioritise the LLIN distributions either before or as soon as possible into local COVID-19 epidemics to mitigate this risk. Additional planning to ensure other malaria prevention activities are continued where possible, alongside planning to ensure basic access to antimalarial treatment, will further minimise the risk of substantial additional malaria mortality.COVID-19 (Disease);Epidemics;Mortality;Malaria

8.
2020.
Non-conventional in English | Homeland Security Digital Library | ID: grc-740234

ABSTRACT

From the Introduction: The Imperial College London COVID-19 [coronavirus disease 2019] Response Team initiated activities of data collation in mid-January, to understand the COVID-19 epidemic in China and its potential impact on other countries. The Imperial Team, together with volunteers, made considerable efforts to collate aggregated data as well as individual patient information from publicly available, national and local situation reports published by health authorities in China. Part of these collated data have been used to inform transmission dynamics and epidemiology of COIVD-19 in several studies of the Team, including disease severity and fatality, phylodynamics in Shandong, and the association between inner-city movement and transmission. We additionally reviewed control measures, school reopening, and work resumption that may relate to the trends across provinces in China. [...] In this report, we publish the collated data and conduct a descriptive analysis of the subnational epidemic trends and interventions. Drawing on epidemic progression and response measures in Chinese provinces affected by COVID-19 early on may provide insights for policy planning in other countries.COVID-19 (Disease);Epidemiology;Public health

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