Application of Information Entropy to Assessment Environmental …
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536.3 thousand people (ANA 2016). It is noteworthy that 5221 families defecated in
the open-air at GD1 in 2013. At GD8, 343 families were in the same situation (SIAB
2013).
The number of households without access to treated water was of 19.54% at GD1
and 28.55% at GD8 in 2013. During the same period, water distribution losses from
the supply networks reached 19.2% and 30.3% at GD1 and GD8, respectively (ANA
2016).
Concerning garbage collection, 14% and 6% of the households did not have their
garbage collected at GD1 and GD8 in 2013, respectively. Improvements in water
quality, basic sanitation and hygiene conditions can reduce diseases, especially in the
most vulnerable age groups, such as children and the elderly (Paiva and Souza 2018).
High infant mortality rates are yet another consequence of inadequate sanitation
conditions. Despite decreasing over the years, infant mortality rates are still high at
both water management units.
The Brazilian sanitation sector displays serious shortcomings, as most institutions
in this sector are unequal and fragmented, due to a decentralized regulatory model
(ABES 2018). In addition, discrepancies between sanitation infrastructures are also
noted. GD8 clearly presents a better infrastructure in relation to GD1, which may
have influenced the information weight of S6 and S7 social subsystem indicators,
which were significantly higher at GD1.
The economic subsystem at GD1 highlighted indicators E2 (Income per capita)
and E5 (Gini index), which measure the degree of inequality in the income distribution of a population, with higher information weights and lower entropy. The
GD8 economic subsystem also highlighted indicator E5. Per capita income increased
slightly over the years, although inequality in income distribution at the two water
management units did not occur linearly throughout the study periods. In 2010, both
GD1 and GD8 achieved the lowest Gini Index or lower inequality in the income
distribution of the population for the analyzed period. The per capita income of
the poorest 10% grew 69% between 2001 and 2009, while the gain was of 12.58%
among the richest 10%. The average per capita income of Brazilians in this period
rose 23.7% in real terms (Neri 2011).
Income distribution is directly related to educational level. Higher incomes per
capita and GDP (Gross Domestic Product) are observed at GD8 when compared to
GD1. The schooling rate (complete elementary school) among people aged 18 years
and over is higher in GD8. Salvato et al. (2010) concluded that the higher the income
percentile considered, the greater the contribution of differences in schooling to differences in income. Moreover, the income dispersion of the poorest regions increases
when the education level of the richest regions is provided, maintaining the salary
profile of the region.
In 2009, hospitalization costs for gastrointestinal infections in the Unified Health
System (SUS) were of about R$ 350 (national average). This led to public expenditures of R$ 161 million in the same year in treating infected people in the hospital
(Instituto Trata Brasil 2018). At GD1, the cost of hospital admissions for waterborne diseases between 2008 and 2014 was of R$ 83,928.59. At GD8, this expense
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536.3 thousand people (ANA 2016). It is noteworthy that 5221 families defecated in
the open-air at GD1 in 2013. At GD8, 343 families were in the same situation (SIAB
2013).
The number of households without access to treated water was of 19.54% at GD1
and 28.55% at GD8 in 2013. During the same period, water distribution losses from
the supply networks reached 19.2% and 30.3% at GD1 and GD8, respectively (ANA
2016).
Concerning garbage collection, 14% and 6% of the households did not have their
garbage collected at GD1 and GD8 in 2013, respectively. Improvements in water
quality, basic sanitation and hygiene conditions can reduce diseases, especially in the
most vulnerable age groups, such as children and the elderly (Paiva and Souza 2018).
High infant mortality rates are yet another consequence of inadequate sanitation
conditions. Despite decreasing over the years, infant mortality rates are still high at
both water management units.
The Brazilian sanitation sector displays serious shortcomings, as most institutions
in this sector are unequal and fragmented, due to a decentralized regulatory model
(ABES 2018). In addition, discrepancies between sanitation infrastructures are also
noted. GD8 clearly presents a better infrastructure in relation to GD1, which may
have influenced the information weight of S6 and S7 social subsystem indicators,
which were significantly higher at GD1.
The economic subsystem at GD1 highlighted indicators E2 (Income per capita)
and E5 (Gini index), which measure the degree of inequality in the income distribution of a population, with higher information weights and lower entropy. The
GD8 economic subsystem also highlighted indicator E5. Per capita income increased
slightly over the years, although inequality in income distribution at the two water
management units did not occur linearly throughout the study periods. In 2010, both
GD1 and GD8 achieved the lowest Gini Index or lower inequality in the income
distribution of the population for the analyzed period. The per capita income of
the poorest 10% grew 69% between 2001 and 2009, while the gain was of 12.58%
among the richest 10%. The average per capita income of Brazilians in this period
rose 23.7% in real terms (Neri 2011).
Income distribution is directly related to educational level. Higher incomes per
capita and GDP (Gross Domestic Product) are observed at GD8 when compared to
GD1. The schooling rate (complete elementary school) among people aged 18 years
and over is higher in GD8. Salvato et al. (2010) concluded that the higher the income
percentile considered, the greater the contribution of differences in schooling to differences in income. Moreover, the income dispersion of the poorest regions increases
when the education level of the richest regions is provided, maintaining the salary
profile of the region.
In 2009, hospitalization costs for gastrointestinal infections in the Unified Health
System (SUS) were of about R$ 350 (national average). This led to public expenditures of R$ 161 million in the same year in treating infected people in the hospital
(Instituto Trata Brasil 2018). At GD1, the cost of hospital admissions for waterborne diseases between 2008 and 2014 was of R$ 83,928.59. At GD8, this expense