Question

Scenario. Big Data predicting the uncertainties A groundbreaking study in Bangladesh has found that using data from mobile phone networks to track movements of people across the country help predict where outbreaks of diseases such as malaria are likely to occur, enabling health authorities to take preventive measures. Every year, malaria kills more than 400,000 people globally and most of them are children. The different type of data, including information provided by the Bangladesh ministry of health, are used to create risk maps indicating the likely locations of malaria outbreaks so the local health authorities can then be warned to take preventative action, including spraying insecticides and stockpiling bed nets and medicines to protect the population from the disease. Questions: 1. It seems malaria is much worse than COVID-19. In order to monitor and control the spread of malaria, how should the data from mobile phone networks be used to conduct predicative analytics and control the disease spread? Justify your answer please. 2. In your answer to question 1, please list at least three major concerns or issues with your proposed approach. (4.5 marks) 3. Australia is using COVIDsafe mobile app to help find close contacts of COVID-19 cases (Brief introduction on COVIDsafe app is available at https://www.health.gov.au/resources/apps-and-tools/covidsafe-app). In comparison to how Bangladesh controls the spread of malaria, please identify at least three key differences between their approach and COVIDsafe app. (4.5 marks) Your answers must be specific to the scenario.

Answer 1

1. The main cause of malaria is the mosquitoes. The increased breeding and spread of mosquitoes can be detected using the sound made by it. Researches has been done to detect the sound of mosquitoes based on their frequency. The buzz sound can be detected and the information can be passed to the mobile phone using the IoT technology. Special applications can be developed for the mobile phones to integrate the detection of mosquitoes number and the prevention of its further spread. Various messages can be organised in the application itself to give warning messages and prevention measures from the spread of diseases. Also using the data of constant monitoring of atmospheric conditions from the satellites, warning messages can be displayed via the applications in the mobile phones. Another method of prevention and control of the disease is the mapping of risk zone areas where malaria can be an epidemic based on the previous data. Also the current place, time and names of the people affected by malaria can also be recorded to predict the occurrence of the malaria using time series analysis or ANN. Finally it can be passed to the mobile phones to inform the common people and the authorities.

2. The above methods has various challenges. Some of them are listed below:

i) Such applications need vast amount of data to map the risk zones and detect the spread.

ii) The people in more localised and rural areas do not have access to modern technoloies like mobile phines, internet etc. So it is difficult to control the disease there.

iii) The system needs a complete integration of various areas like geology, networking, wather forecasting etc.

3.

i) COVIDSafe application is an application that does not use much technical knowledge. It only identifies the people's contact and finally detecting the diseases.

ii) In COVIDSafe method, the health officials play an important role in perceiving the details of the app whereas in Bangladesh health officials are much less bothered about the application.

iii)The emergence of resistance to artemisinin-based combination therapies, front-line antimalarials key to malaria control was the biggest contribution in Bangaldesh whereas COVIDSafe app plays only outside the medical field and provide assistance.