PMC:7797241 / 36044-36704 JSONTXT

{"project":"LitCovid-sentences","denotations":[{"id":"T210","span":{"begin":0,"end":212},"obj":"Sentence"},{"id":"T211","span":{"begin":213,"end":392},"obj":"Sentence"},{"id":"T212","span":{"begin":393,"end":660},"obj":"Sentence"}],"namespaces":[{"prefix":"_base","uri":"http://pubannotation.org/ontology/tao.owl#"}],"text":"With this in mind, our findings demonstrate that there are still significant data gaps—and in the absence of such data, mathematical models can provide a valuable asset for local and regional healthcare services. This regional model will be used further in the SW as the pandemic evolves and could be used within other healthcare systems in other geographies to support localised predictions. Controlling intervention measures at a more local level could be made possible through monitoring and assessment at the regional level through a combination of clinical expertise and local policy, guided by localised predictive forecasting as presented in this study."}