Page 28 - Contributed Paper Session (CPS) - Volume 3

CPS1934 Atikur R. K. et al.
morbidity and mortality, which results in increased use of health services and
hospital admissions. Respiratory disease incidence are correlated with climatic
factors including temperature, relative humidity and other air pollution related
consequences. According to WHO (2014), there were almost 7 million
premature death in 2012 as consequences of air pollution and 88% of those
deaths were in developing countries. Being a developing country, Bangladesh
is achieving a very fast growth in economic and infrastructure development
with the cost of increasing air pollution and climatic changes. Increasing air
pollution and fluctuation in climatic patterns are likely to increase the RTI
incidences with increasing burden in healthcare services. Thus it is important
to know the severity of RTI episodes well before in time for healthcare
planning and management. In this paper, we explore the relationship between
RTI episodes extracted from millions of prescriptions and climatic factors
obtained from 35 weather stations in Bangladesh, and predict the number of
daily RTI episodes by using panel generalized linear models, regression tree
and random forest.
Our study design based on the integration of prescription data and
climatic factors from 35 weather zones defined by 35 active weather stations
in Bangladesh is the first of its kind in a developing country context. Though
several studies have been done in other countries with hospital records and
climatic factors, most of those research have used weekly or monthly data
without considering time lag relationship between daily RTI episodes and
climatic factors. In a recent study in Shenmu County of China, Liu et al. (2016)
have analyzed meteorological data and medical data from hospitalized
patients less than 16 years of age and have found that the meteorological
factors (air temperature, atmospheric pressure, rainfall, hours of sunlight, wind
speed and relative humidity) are significantly associated with the lower
respiratory tract infection (LRTI). Pearson correlation and multiple linear
regression models have been used to explore the relationship between LRTI
episodes and climatic factors. The LRTI does not happen instantly, there is a
burn-in period since microorganism or viruses get into the body, and this
burn-in period depends on the immune system and level of resistance of body.
Thus a time lag relationship between climatic factors and disease incidence
needs to be considered to explore the effect of climatic factors on LRTI
episodes.
It is not only the level of temperature, oscillation of temperature is more
sensitive to at-risk group (elderly, children, infants, and patients with medical
conditions). Older adults and children are more vulnerable to daily
temperature oscillations (Xu et al., 2012). An Australian study showed a
correlation between sharp temperature change between two neighboring
days and increased emergency visits for childhood pneumonia, and this effect
can last up to 3 weeks (Xu, Hu and Tong, 2014). This findings also support to

17 | I S I W S C 2 0 1 9