‘Real-time snapshot of epidemic trends worldwide’
Imperial researchers have developed a new forecasting tool to support global outbreak monitoring for COVID-19 and other deadly diseases.
The project, Mapping the Risk of International Infectious Disease Spread (MRIIDS), aims to inform key health decision-makers at national and regional levels of the risks of an epidemic spreading in real-time, and aids government and non-governmental decision-makers as they prepare for the possible arrival of an infectious disease threat to their region.
Predicting the number of daily cases or deaths
The user-friendly tool is designed to both forecast case counts during infectious disease outbreaks and also estimate the risk of infectious disease cases arriving from and departing to specific geographic areas.
The cloud-based tool is reshaping current forecasting methods by automating the integration of different open-access data streams to inform infectious disease outbreak forecasting algorithms in near real-time.
The tool was initially designed and based on the 2014-16 West Africa Ebola outbreak, but is currently being used to produce weekly global COVID-19 forecasts.
‘Real-time snapshot of epidemic trends worldwide’
Dr Anne Cori, from the School of Public Health, said: “In MRIIDS 2.0, we have implemented a generic epidemic forecasting method, which relies solely on open access data and opensource code. Currently we are using it to produce global COVID-19 forecasts every week, providing a real-time snapshot of epidemic trends worldwide. But most importantly we have designed an infrastructure that is ready in advance of the next epidemic to enable an early and continuous risk assessment.”
Dr Sangeeta Bhatia, from the School of Public Health, said: “Our goal with MRIIDS 2.0 is to develop an analysis pipeline – from ingesting data, feeding them into transmission models, to visualising the outputs – that can be reused to answer questions about infectious disease spread. We hope that this tool will serve as a central resource for infectious disease forecasting in the future”
Dr Pierre Nouvellet, visiting academic at the School of Public Health, said: “While forecasting the spread of infectious disease is essential for public health and policy planning, we still lag behind forecasting infrastructures seen in meteorology, for instance. With MRIIDS 2.0, we are getting a step closer by integrating advances in our understanding of disease spread, advances in statistical modelling, and, not least, advances in data availability.”
Dr Britta Lassmann, former program director at the International Society for Infectious Diseases, said: “With MRIIDS 2.0, we are one step closer to real-time infectious disease outbreak forecasting. Our tool enables data-driven responses for policymakers and individuals globally, allowing resource allocation tailored to the risk level in a country or region.”
To explore the platform, visit www.mriids.org. The Methodology for this was peer reviewed and published in Nature.
Original Article: Real-time epidemic forecasting tool to support global outbreak monitoring
More from: Imperial College London | International Society for Infectious Diseases | University of Sussex | University of California Davis | Boston Children’s Hospital | Harvard Medical School
The Latest Updates from Bing News & Google News
Go deeper with Bing News on:
Outbreak monitoring
- Animal lovers 'in tears' as wildlife services 'struggle to cope' amid bird flu outbreak
WILDLIFE services are “struggling to cope” after underfunding, the founder of one of the county’s biggest wildlife hospitals has said.
- Denmark hit by a trio of Listeria outbreaks with unknown sources; eight deaths reported
so the outbreak could be stopped. Fødevarestyrelsen has written to a number of large industry organizations calling for their members to sharpen in-house monitoring of Listeria. If they find the ...
- Florida meningococcal outbreak among gay and bisexual men is one of worst in US history: CDC
Federal and state health officials in Florida are looking into an illness cause by bacteria called meningococcal, which has killed 6 so far according to the CDC.
- CDC monitoring outbreak of Meningococcal disease in Florida: The symptoms to watch for
Health officials are monitoring an outbreak of meningococcal disease in Florida. Here are the symptoms to watch for.
- This outbreak simulator predicted the strange twists in our pandemic behavior
“It’s insane how much we have to overcome to get to a point where this will work and these technologies [such as contact tracing and health-monitoring apps] won’t be scary to people.” Sabeti estimates ...
Go deeper with Google Headlines on:
Outbreak monitoring
Go deeper with Bing News on:
Real-time infectious disease outbreak forecasting
- This outbreak simulator predicted the strange twists in our pandemic behavior
Sabeti had previously researched infectious diseases ... Operation Outbreak Every interaction and contact that happens during the simulation is recorded into a web server that can be used to observe ...
- The role of smartphone apps during the COVID-19 pandemic
In a recent study published in Nature Biotechnology, researchers assessed the role of smartphone apps during the coronavirus disease 2019 (COVID-19) pandemic.
- Antibody Testing Market Forecast to 2028 - COVID-19 Impact and Global Analysis By Products, Indication, End User
The global antibody testing market was valued at US$ million 7,260. 00 in 2021 and is projected to reach US$ 11,578. 47 million by 2028; it is expected to grow at a CAGR of 6. 9% from 2021 to 2028.New ...
- Coronavirus vaccines for kids under 5 are finally here
The Food and Drug Administration has authorized and the Centers for Disease ... provide real-time data on the coronavirus and future outbreaks — a ‘National Weather Service’ to forecast ...
- PCR & Real-time PCR Molecular Diagnostics Market Drivers, Demand and Growth Prospect 2021 to 2027
Global PCR & Real-time PCR ... in prevalence of infectious diseases, and growing focus on research & development activities would drive the growth of the market during the forecast period of ...
