Most water sources in Nusa Tenggara Timur contain higher concentration of calcium and magnesium ions, which is known as hard water. Long-term consumption of hard water can cause kidney dysfunction, which may lead to the other diseases such as cerebrovascular disease, diabetes and others. Therefore, understanding the effects of hard water consumption on kidney function is of importance. This paper studies the transmission dynamics of kidney dysfunction due to the consumption of hard water using a mathematical model. We propose a new deterministic mathematical model comprising human and water compartments and conduct a global sensitivity analysis to determine the most influential parameters of the model. The Routh-Hurwitz criterion is used to examine the stability of the steady states. The results shows that the model has two steady states, which are locally stable. Moreover, we found that the most influential parameters are the maximum concentration of magnesium and calcium in the water, the increase rate of calcium and magnesium concentration in the water and the rate of effectiveness of water treatment. The results suggest that better water treatments are required to reduce the concentration of magnesium and calcium in the water. This aid in minimizing the probability of humans to attract kidney dysfunction. Furthermore, water-related data need to be collected for further investigation.

1.
P.
Sengupta
.
Potential health impacts of hard water
.
International Journal of Preventive Medicine
,
4
:
866
875
,
2013
.
2.
CY
Yang
,
MF
Cheng
,
SS
Tsai
, and
YL
Hsieh
.
Calcium, magnesium, and nitrate in drinking water and gastric cancer mortality
.
Japanese Journal of Cancer Research GANN
,
89
:
124
130
,
1998
.
3.
G.
Abraham
,
S.
Varughese
,
T.
Thandavan
,
A.
Iyengar
,
E.
Fernando
,
S.A. J.
Naqvi
,
R.
Sheriff
,
H.
Ur-Rashid
,
N.
Gopalakrishnan
, and
R. K.
Kafle
.
Chronic kidney disease hotspots in developing countries in South Asia
.
Clinical Kidney Journal
,
9
(
1
):
135
141
,
2016
.
4.
Badan Penelitian dan Pengembangan Kesehatan. Kementrian Kesehatan Republik Indonesia.
Riset Kesehatan Dasar 2013. http://www.depkes.go.id/resources/download/general/Hasil Online; accessed 8 December 2017.
5.
M. Z.
Ndii
,
D.
Allingham
,
R. I.
Hickson
, and
K.
Glass
.
The effect of Wolbachia on dengue dynamics in the presence of two serotypes of dengue: symmetric and asymmetric epidemiological characteristics
.
Epidemiology and Infection
,
144
(
13
):
2874
2882
,
2016
.
6.
M.
Andraud
,
N.
Hens
,
C.
Marais
, and
P.
Beutels
.
Dynamic epidemiological models for dengue transmission: A systematic review of structural approaches
.
PLOS ONE
,
7
(
11
):
1
14
, 11
2012
.
7.
M. Z.
Ndii
.
Mathematical modelling to investigate a Wolbachia intervention to reduce dengue transmission
. PhD thesis,
Department of Mathematics, The University of Newcastle
,
2015
.
8.
M. Z.
Ndii
,
Z.
Amarti
,
E. D.
Wiraningsih
, and
A. K.
Supriatna
.
Rabies epidemic model with uncertainty in parameters: Crisp and fuzzy approaches
.
IOP Conference Proceeding
,
2018
.
9.
M. Z.
Ndii
,
N.
Anggriani
, and
A. K.
Supriatna
.
Application of diffierential transformation method for solving dengue transmission mathematical model
.
Symposium on Biomathematics
.
AIP Conference Proceeding
,
2018
.
10.
N.
Chitnis
,
J. M.
Hyman
, and
J. M.
Cushing
.
Determining important parameters in the spread of malaria through the sensitivity analysis of a mathematical model
.
Bulletin of Mathematical Biology
,
70
(
5
):
1272
,
2008
.
11.
M. Z.
Ndii
,
D.
Allingham
,
R.I.
Hickson
, and
K.
Glass
.
The effect of Wolbachia on dengue outbreaks when dengue is repeatedly introduced
.
Theoretical Population Biology
,
111
:
9
15
,
2016
.
12.
M. Z.
Ndii
and
A.K.
Supriatna
.
Stochastic mathematical models in epidemiology
.
Information
,
20
:
6185
6196
,
2017
.
13.
W.
Hao
,
B.H.
Rovin
, and
A.
Friedman
.
Mathematical model of renal interstitial fibrosis
.
Proceedings of the National Academy of Sciences
,
111
(
39
):
14193
14198
,
2014
.
14.
J.
Lin
,
E. L.
Knight
,
M.L.
Hogan
, and
A. K.
Singh
.
A comparison of prediction equations for estimating glomerular filtration rate in adults without kidney disease
.
Journal of the American Society of Nephrology
,
14
(
10
):
2573
2580
,
2003
.
15.
J.S.
Clemmer
,
W.A.
Pruett
,
T.G.
Coleman
,
J.E.
Hall
, and
R.L.
Hester
.
Mechanisms of blood pressure salt sensitivity: new insights from mathematical modeling
.
American Journal of Physiology - Regulatory, Integrative and Comparative Physiology
,
312
(
4
):
R451
R466
,
2017
.
16.
Freedman
BS
.
Modeling kidney disease with ips cells
.
Biomarker Insights
,
10
:
153
169
,
2015
.
17.
D.
Haris
.
Quantitative Chemical Analysis
.
W.H. Freeman and Company
,
New York
,
2010
.
18.
S.
Marino
,
I. B.
Hogue
,
C. J.
Ray
, and
D. E.
Kirschner
.
A methodology for performing global uncertainty and sensitivity analysis in systems biology
.
Journal of Theoretical Biology
,
254
(
1
):
178
196
,
2008
.
19.
R. U.
Hurint
,
M. Z.
Ndii
, and
M.
Lobo
.
Analisis sensitivitas dari model epidemi SEIR
.
Natural Science: Journal of Science and Technology
,
6
(
1
):
22
28
,
2017
.
20.
M. A.
Sanchez
and
Sally M.
Blower
.
Uncertainty and sensitivity analysis of the basic reproductive rate. tuberculosis as an example
.
Americal Journal of Epidemiology
,
145
(
12
):
1127
1137
,
1997
.
21.
M. Z.
Ndii
,
R. I.
Hickson
, and
G. N.
Mercer
.
Modelling the introduction of Wolbachia into Aedes aegypti to reduce dengue transmission
.
The ANZIAM Journal
,
53
:
213
227
,
2012
.
22.
M. Z.
Ndii
,
R. I.
Hickson
,
D.
Allingham
, and
G. N.
Mercer
.
Modelling the transmission dynamics of dengue in the presence of Wolbachia
.
Mathematical Biosciences
,
262
:
157
166
,
2015
.
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