{"id":224,"date":"2020-10-01T14:39:57","date_gmt":"2020-10-01T14:39:57","guid":{"rendered":"http:\/\/localhost.ona\/?post_type=case-study&#038;p=224"},"modified":"2024-02-28T15:37:32","modified_gmt":"2024-02-28T20:37:32","slug":"saving-lives-and-livelihoods-through-comprehensive-multi-agency-data-systems-and-design","status":"publish","type":"case-study","link":"https:\/\/ona.io\/home\/case-study\/saving-lives-and-livelihoods-through-comprehensive-multi-agency-data-systems-and-design\/","title":{"rendered":"Saving Lives and Livelihoods through Multi-Agency Data Systems"},"content":{"rendered":"<h5><b>Goal<\/b><\/h5>\n<p>Aggregate multi-party, cross-region data to better inform local and national response planning capacity after a natural disaster.<\/p>\n<h5><b>Brief<\/b><\/h5>\n<p>In March 2019, Cyclone Idai hit Southeast Africa. Reportedly <a href=\"https:\/\/www.nytimes.com\/2019\/03\/19\/world\/africa\/cyclone-idai-mozambique.html\">one of the deadliest tropical storms<\/a> to hit the southern hemisphere, the cyclone pummeled Mozambique, Zimbabwe, and Malawi resulting in a humanitarian disaster throughout the region. Devastating winds up to 120kph, along with heavy rains,\u00a0 flooding, and landslides, left dozens of lives lost, thousands injured and a trail of property destroyed.<\/p>\n<p>The governments of Mozambique, Malawi, and Zimbabwe, and the humanitarian community responded swiftly with Malawi and Zimbabwe declaring a state of emergency in the affected areas and the United Nations categorizing the emergency at Level 3 (L3). The coordinated response resulted in a host of governments, the UN, and other international humanitarian agencies sending emergency response teams to the affected areas.<\/p>\n<p>Disaster relief organizations needed rapid and coherent responses amongst the different players in the region, specifically in the form of access to accurate and real-time data across many response activities. Disaggregated approaches to data collection and visualization created siloed information, which limited data sharing between partners and coordinating agencies, making them unable to cross-analyze information.<\/p>\n","protected":false},"featured_media":1042,"template":"","acf":[],"_links":{"self":[{"href":"https:\/\/ona.io\/home\/wp-json\/wp\/v2\/case-study\/224"}],"collection":[{"href":"https:\/\/ona.io\/home\/wp-json\/wp\/v2\/case-study"}],"about":[{"href":"https:\/\/ona.io\/home\/wp-json\/wp\/v2\/types\/case-study"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/ona.io\/home\/wp-json\/wp\/v2\/media\/1042"}],"wp:attachment":[{"href":"https:\/\/ona.io\/home\/wp-json\/wp\/v2\/media?parent=224"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}