A Cloud Based Disease Surveillance and Health Information System

Abstract

Outbreaks can overwhelm weak or fragile health systems that lack the tools, infrastructure, policies, and systems to keep communities healthy and safe. Timely detection, preparedness, and appropriate response are essential for limiting both the loss of human life and crippling political and socio-economic impact of disease outbreaks. Countries must build effective and sustainable disease surveillance and reporting systems that mobilize all levels of the health system including, communities for crisis response. In Pakistan, currently there is no health information and diseases surveillance system. National Institute of Health has been given the task to detect disease outbreak (both current and future) and prepare appropriate response against it. The current disease surveillance system is completely manual. Diseases are being reported by sending hard copies or using the email system. Most of the disease outbreaks are being reported by the print and electronic media while the government has no or very limited information for the reported outbreak. This ineffective reporting system not only creates problems in managing the counter measures against a disease outbreak but is likely to cause a mass hysteria amongst the people. District Health Information Software 2 (DHIS2) is an open source, web based software developed by University of Oslo and can be deployed in Pakistan for Disease surveillance and Health Information Management. It is being deployed worldwide in many countries and some institutions like the European Union (EU), and World Health Organization. A total of around 47 countries, both developed and under developed are in the deployment phases of DHIS-2. DHIS2 is not only a disease surveillance tool but is also used to process statistical data, validate the data, analyze and present it. Its data analytics and management platform is completely web-based and boasts great visualization features. The software has ability to create analysis from live data in seconds