{"id":861219,"date":"2022-07-12T03:03:22","date_gmt":"2022-07-12T10:03:22","guid":{"rendered":"https:\/\/www.microsoft.com\/en-us\/research\/"},"modified":"2022-07-13T00:22:10","modified_gmt":"2022-07-13T07:22:10","slug":"active-syndromic-surveillance-of-covid-19-in-israel","status":"publish","type":"msr-research-item","link":"https:\/\/www.microsoft.com\/en-us\/research\/publication\/active-syndromic-surveillance-of-covid-19-in-israel\/","title":{"rendered":"Active syndromic surveillance of COVID-19 in Israel"},"content":{"rendered":"

Syndromic surveillance systems monitor disease indicators to detect emergence of diseases and track their progression. Here, we report on a rapidly deployed active syndromic surveillance system for tracking COVID-19 in Israel. The system was a novel combination of active and passive components: Ads were shown to people searching for COVID-19 symptoms on the Google search engine. Those who clicked on the ads were referred to a chat bot which helped them decide whether they needed urgent medical care. Through its conversion optimization mechanism, the ad system was guided to focus on those people who required such care. Over 6 months, the ads were shown approximately 214,000 times and clicked on 12,000 times, and 722 people were informed they needed urgent care. Click rates on ads and the fraction of people deemed to require urgent care were correlated with the hospitalization rate (R<\/mi>2<\/mn><\/msup>=<\/mo>0.54<\/mn><\/math>\">R<\/span>2<\/span><\/span>=<\/span>0.54<\/span><\/span><\/span><\/span><\/span><\/p>\n

R<\/mi>2<\/mn><\/msup>=<\/mo>0.54<\/mn><\/math><\/p>\n

and\u00a0R<\/mi>2<\/mn><\/msup>=<\/mo>0.50<\/mn><\/math>\">R<\/span>2<\/span><\/span>=<\/span>0.50<\/span><\/span><\/span><\/span><\/span><\/p>\n

R<\/mi>2<\/mn><\/msup>=<\/mo>0.50<\/mn><\/math><\/p>\n

, respectively) with a lead time of 9 days. Males and younger people were more likely to use the system, and younger people were more likely to be determined to require urgent care (slope:\u00a0\u2212<\/mo>0.009<\/mn><\/math>\">\u2212<\/span><\/span>0.009<\/span><\/span><\/span><\/span><\/span><\/p>\n

\u2212<\/mo><\/mspace>0.009<\/mn><\/math><\/p>\n

,\u00a0P<\/mi>=<\/mo>0.01<\/mn><\/math>\">P<\/span>=<\/span>0.01<\/span><\/span><\/span><\/span><\/span><\/p>\n

P<\/mi>=<\/mo>0.01<\/mn><\/math><\/p>\n

). Thus, the system can assist in predicting case numbers and hospital load at a significant lead time and, simultaneously, help people determine if they need medical care.<\/p>\n","protected":false},"excerpt":{"rendered":"

Syndromic surveillance systems monitor disease indicators to detect emergence of diseases and track their progression. Here, we report on a rapidly deployed active syndromic surveillance system for tracking COVID-19 in Israel. The system was a novel combination of active and passive components: Ads were shown to people searching for COVID-19 symptoms on the Google search […]<\/p>\n","protected":false},"featured_media":0,"template":"","meta":{"msr-url-field":"","msr-podcast-episode":"","msrModifiedDate":"","msrModifiedDateEnabled":false,"ep_exclude_from_search":false,"_classifai_error":"","footnotes":""},"msr-content-type":[3],"msr-research-highlight":[],"research-area":[13556,13553],"msr-publication-type":[193715],"msr-product-type":[],"msr-focus-area":[],"msr-platform":[],"msr-download-source":[],"msr-locale":[268875],"msr-post-option":[],"msr-field-of-study":[],"msr-conference":[],"msr-journal":[262384],"msr-impact-theme":[],"msr-pillar":[],"class_list":["post-861219","msr-research-item","type-msr-research-item","status-publish","hentry","msr-research-area-artificial-intelligence","msr-research-area-medical-health-genomics","msr-locale-en_us"],"msr_publishername":"","msr_edition":"","msr_affiliation":"","msr_published_date":"2021-12-27","msr_host":"","msr_duration":"","msr_version":"","msr_speaker":"","msr_other_contributors":"","msr_booktitle":"","msr_pages_string":"","msr_chapter":"","msr_isbn":"","msr_journal":"","msr_volume":"","msr_number":"","msr_editors":"","msr_series":"","msr_issue":"","msr_organization":"","msr_how_published":"","msr_notes":"","msr_highlight_text":"","msr_release_tracker_id":"","msr_original_fields_of_study":"","msr_download_urls":"","msr_external_url":"","msr_secondary_video_url":"","msr_longbiography":"","msr_microsoftintellectualproperty":1,"msr_main_download":"","msr_publicationurl":"","msr_doi":"","msr_publication_uploader":[{"type":"url","viewUrl":"false","id":"false","title":"https:\/\/www.nature.com\/articles\/s41598-021-03977-3","label_id":"243109","label":0}],"msr_related_uploader":"","msr_attachments":[],"msr-author-ordering":[{"type":"user_nicename","value":"Elad Yom-Tov","user_id":31729,"rest_url":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/microsoft-research\/v1\/researchers?person=Elad Yom-Tov"}],"msr_impact_theme":[],"msr_research_lab":[199563],"msr_event":[],"msr_group":[916890],"msr_project":[918255,375953],"publication":[],"video":[],"download":[],"msr_publication_type":"article","related_content":{"projects":[{"ID":918255,"post_title":"Global response & information","post_name":"global-response-information","post_type":"msr-project","post_date":"2023-10-25 20:53:06","post_modified":"2023-10-26 14:22:31","post_status":"publish","permalink":"https:\/\/www.microsoft.com\/en-us\/research\/project\/global-response-information\/","post_excerpt":"The COVID-19 pandemic has affected nearly every aspect of life around the world, from healthcare and economics to diet and social needs. As a result, researchers have turned to a variety of methods to understand the impacts of the pandemic and inform policies and recovery efforts. These methods include analyzing internet search data to track shifts in human needs and dietary interests, using self-supervised learning to improve vertical search in the biomedical literature, and studying…","_links":{"self":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-project\/918255"}]}},{"ID":375953,"post_title":"Internet-Mediated Health","post_name":"internet-mediated-health","post_type":"msr-project","post_date":"2012-08-01 05:15:47","post_modified":"2022-07-14 02:17:04","post_status":"publish","permalink":"https:\/\/www.microsoft.com\/en-us\/research\/project\/internet-mediated-health\/","post_excerpt":"The majority of Internet users turn to the web for information when they have a medical concern. The data generated while users seek such information, and more generally when they browse the Internet for work and pleasure, represent a potential boon for medical research. During the past decade these data have proven valuable where the most patient activity happens online, where internet data provides a more sensitive indicator than that attainable from traditional sources, and…","_links":{"self":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-project\/375953"}]}}]},"_links":{"self":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-research-item\/861219","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-research-item"}],"about":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/types\/msr-research-item"}],"version-history":[{"count":2,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-research-item\/861219\/revisions"}],"predecessor-version":[{"id":861792,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-research-item\/861219\/revisions\/861792"}],"wp:attachment":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/media?parent=861219"}],"wp:term":[{"taxonomy":"msr-content-type","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-content-type?post=861219"},{"taxonomy":"msr-research-highlight","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-research-highlight?post=861219"},{"taxonomy":"msr-research-area","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/research-area?post=861219"},{"taxonomy":"msr-publication-type","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-publication-type?post=861219"},{"taxonomy":"msr-product-type","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-product-type?post=861219"},{"taxonomy":"msr-focus-area","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-focus-area?post=861219"},{"taxonomy":"msr-platform","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-platform?post=861219"},{"taxonomy":"msr-download-source","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-download-source?post=861219"},{"taxonomy":"msr-locale","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-locale?post=861219"},{"taxonomy":"msr-post-option","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-post-option?post=861219"},{"taxonomy":"msr-field-of-study","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-field-of-study?post=861219"},{"taxonomy":"msr-conference","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-conference?post=861219"},{"taxonomy":"msr-journal","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-journal?post=861219"},{"taxonomy":"msr-impact-theme","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-impact-theme?post=861219"},{"taxonomy":"msr-pillar","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-pillar?post=861219"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}