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1. MONITORING HAZE PHENOMENON AND ITS EFFECT
ON HAZE-BORNE DISEASES
NORLISA AHMADTERMIZI1, MD. KHADZIR SHEIKH AHMAD2, HAMMAD FAHLI SIDEK2,ANIS AFIRAH MOHAMAD RADHI1,
MUHAMMAD AIMAN MAZLAN1 ANDWAN ZAWAWI MD ZIN1
1DATA ANALYTICS SOLUTIONS, CORPORATE TECHNOLOGY, MIMOS BERHAD
2HEALTH INFORMATICS CENTRE, PLANNING DIVISION, MINISTRY OF HEALTH MALAYSIA
Abstract
Malaysia was affected by haze with 25 locations registering
‘unhealthy’ Air Pollutant Index (API) readings beginning September
2019 leading into October 2019. This was mainly attributed to
large-scale forest fires and biomass burning which are the major
aerosol sources that may affect population health where asthma,
conjunctivitis and upper respiratory tract infection are among the
most common diseases. This study used spatial information derived
from remotely sensed data and geographical information system to
understand the relationship between health conditions, in addition
to locating and forecasting haze-borne disease outbreaks. The
combination of near real-time visible bands and Aerosol Optical
Depth (AOD) from MODIS/Terra Aerosol, and the inpatient
discharge data from hospitals are visualized in the GIS web
application to monitor the aerosol’s concentration and
characteristics retrievals during the haze incident. The web
application displays several variables related to inpatient discharge
by the hospital with the combination of API readings within
Malaysia. Monitoring the inpatient discharge after the incident is
important for the government and private sector to take
precautionary measures especially in health effects if this incident
happens again in the future.
Introduction
Good health is important to lead a successful life and to be
more productive in performing daily activities. However, human
activities lead to air pollution, where the aerosols are hazardous
to human health, limit visibility and cause haze occurrences all
over the world.
Large-scale forest fires [1] and biomass burning [2] are the
major aerosol sources for haze in Malaysia in September 2019.
This phenomenon has forced Malaysian authorities to take
measures such as to close down schools as wind continued to
blow the haze coming from Kalimantan and Sumatra in Indonesia
into Malaysia [3 and 4] with API readings hovering in the 200-300
range.
During the same period, hospitals and clinics reported a spike
in the number of patients seeking treatment with about 40%
increase [5]. Exposure to the haze can lead to cough and
respiratory infection and other haze-borne diseases [6].
An integrated geo-spatial technology like geographic
information system (GIS) and remote sensing can contribute
substantially in an interactive visualization for better
understandings in monitoring haze phenomenon and its effect to
the haze-borne diseases. GIS approach includes database
management, planning, risk area mapping and location
identification [7] while recent advances in atmospheric remote
sensing offer a unique opportunity using satellite sensors in
determining the aerosol optical depth and air quality.
Methodology
Visit data from all government and private healthcare facilities
and services are collected and kept in one structured system built
for query and analytic purposes known as Malaysia Health Data
Warehouse (MyHDW) [8]. It includes a patient treatment
information system and patient registry information system.
In order to detect patterns, trends and allow prediction, a GIS
dashboard is used to support an alternative administration for
targeted users to plan for and manage resource requests. Three
main haze-borne diseases (asthma, conjunctivitis and upper
respiratory tract infection) are summarized into the meaningful
Conclusion
As a conclusion, map-based representations using GIS and
remote sensing with the combination of healthcare data for the
haze phenomenon and its effect to haze-borne diseases are
crucial for supporting spatial thinking and maintaining situation
awareness among Malaysian as a monitoring and evaluation tool.
10th IGRSM International Conference and Exhibition on Geospatial & Remote Sensing
October 20-21, 2020, Kuala Lumpur, Malaysia
References
1. Urbanski, Shawn P., Wei Min Hao, and Stephen Baker. "Chemical composition of wildland fire emissions." Developments in Environmental
Science 8 (2008): 79-107.
2. Popovicheva, Olga, et al. "Aerosol in emissions of Siberian biomass burning: Small-scale fire study." ProScience 1 (2014): 405-410.
3. The Straits Times, 2019. Haze blankets much of Malaysia. Retrieved February 17, 2019 from https://www.straitstimes.com/asia/se-asia/haze-
blankets-much-of-malaysia
4. Hanafi, Nur H., Mimi Haryani Hassim, and Zainura Z. Noor. "Overview of Health Impacts due to Haze Pollution in Johor, Malaysia." Journal of
Engineering and Technological Sciences 50.6 (2018): 818-831.
5. New Straits Times, 2019. Haze crisis: Haze-related illnesses soar by 40 per cent. Retrieved February 17, 2019 from
https://www.nst.com.my/news/nation/2019/09/523636/haze-crisis-haze-related-illnesses-soar-40-cent
6. Channel News Asia, 2019. More people fall sick as haze worsens in Malaysia. Retrieved February 17, 2019 from
https://www.channelnewsasia.com/news/asia/malaysia-haze-fall-sick-patients-respiratory-problems-fires-11902668)
7. Sharma, Ashok Kumar. "Role of GIS in Health Management Information System and Medical Plan: A Case Study of Gangtok area, Sikkim,
India." International Journal of Environment and Geoinformatics 2.1 (2015): 16-24.
8. Ministry of Health Malaysian Health Data Warehouse MyHDW 2015-2016 Start up: Initiation Available at:
https://myhdw.moh.gov.my/public/documents/
IGRSM 2020
Results & Discussion
In Figure 2, a dashboard entitled ‘Haze-Borne Diseases’ is
represented. The dashboard is captured on 22nd September
where it shows high API and contains information of patient
discharge by age group, discipline and gender.
For asthma cases, the total count increased day by day. From the
line chart, it can be seen that most of the patient discharge is
from the age group of <1 year and age group between 5-9 years.
Based on the patient discharge by gender, woman patient is
higher compared to man patient. Based on the time series
animation, the AOD increases to greater than 3.0, which means
aerosol become so dense that sun is obscured at that stage.
It is advisable to those who have a higher risk of being
affected by the haze to remain indoors. Children and the elderly
should avoid prolonged exposure to the haze. In addition,
pregnant women should reduce exposure to haze for the health
of their unborn baby.
information combined with spatial data derived from MyHDW.
The air pollutant index (API) derived from Air Pollutant Index
of Malaysia website is integrated in the dashboard in order to
visualize the real-time API during the haze period. Moreover, for
visualization purposes, the near real-time visible bands and
Aerosol Optical Depth (AOD) from MODIS/Terra Aerosol layers
from NASA’s Worldview browser are used to indicates the level
at which particles in the air (aerosols) prevent light from traveling
through the atmosphere from September 1, 2019 to September
30, 2019. An overview of the complete steps for this paper is
illustrated in Figure 1 below.
Figure 1: Process overview
Figure 2: Haze-Borne Diseases Dashboard
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