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\begin{document}

\title{The Association between Rainfall, Temperature and Reported Drinking
Water Source: A Multi-Country Analysis}



\author[1]{Andrea Buchwald}%
\author[2]{Evan Thomas}%
\author[2]{Kristopher B Karnauskas}%
\author[1]{Elise Grover}%
\author[3]{Karen L Kotloff}%
\author[1]{Elizabeth J Carlton}%
\affil[1]{Colorado School of Public Health}%
\affil[2]{University of Colorado Boulder}%
\affil[3]{Department of Pediatrics, University of Maryland School of Medicine}%


\vspace{-1em}



  
  \date{June 07, 2024}


\begingroup
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\selectlanguage{english}
\begin{abstract}
Climate change may alter access to safe drinking water, with important
implications for health. We assessed the relationship between
temperature and rainfall and utilization of basic drinking water (BDW)
in The Gambia, Mozambique, Pakistan, and Kenya. The outcomes of interest
were 1) whether the reported drinking water source used in the past two
weeks met the World Health Organization definition of BDW and 2) use of
a BDW source that was always available. Temperature and precipitation
data were compiled from weather stations and satellite data and
summarized to account for long- and short-term weather patterns and
lags. We utilized random forests and logistic regression to identify key
weather variables that predicted outcomes by site and the association
between important weather variables and BDW use. Higher temperatures
were associated with decreased BDW use at three of four sites and
decreased use of BDW that is always available at all four sites.
Rainfall, both in the long- and short-term, was associated with
increased BDW use in three sites. We found evidence for interactions
between household wealth and weather variables at two sites, suggesting
lower wealth populations may be more sensitive to weather-driven changes
in water access. Changes in temperature and precipitation can alter safe
water use in low-resource settings -- investigating drivers for these
relationships can inform efforts to build climate resilience.%
\end{abstract}%



\sloppy


\textbf{Table 1. Description of drinking water use and general
characteristics of the GEMS study sites. Countries with sufficient
variability (\emph{\textgreater{}}10\% and \emph{\textless{}}90\% of
observations with Outcome 1 or Outcome 2) in the primary and secondary
outcome to be included in analysis, are indicated in bold.}\selectlanguage{english}
\begin{longtable}[]{@{}llllllll@{}}
\toprule
& \textbf{Gambia} & Mali & \textbf{Mozambique} & \textbf{Kenya} & India
& Bangladesh & \textbf{Pakistan}\tabularnewline
\midrule
\endhead
Number of Participants & \textbf{2,598} & 4,097 & \textbf{1,976} &
\textbf{3,359} & 3,582 & 3,859 & \textbf{3,096}\tabularnewline
Study Site Characteristics & & & & & & &\tabularnewline
Rural/Urban & \textbf{Rural} & Urban & \textbf{Rural} & \textbf{Rural} &
Urban & Rural & \textbf{Urban}\tabularnewline
Population at risk & \textbf{29,076} & 31,768 & \textbf{15,380} &
\textbf{21,603} & 13,416 & 25,560 & \textbf{25,659}\tabularnewline
Area (km\textsuperscript{2}) & \textbf{1,084} & 16 & \textbf{500} &
\textbf{500} & 10.5 & 374 & \textbf{10}\tabularnewline
Outcomes & & & & & & &\tabularnewline
Main source of water is an improved water source* & \textbf{85.0} & 99.9
& \textbf{82.6} & \textbf{62.6} & 98.6 & 99.8 &
\textbf{95.2}\tabularnewline
More than 30 minutes wait time for main source of water & \textbf{8.6} &
2.6 & \textbf{15.9} & \textbf{19.7} & 8.4 & 0.1 &
\textbf{19.3}\tabularnewline
Main source of water is always available & \textbf{54.2} & 94.3 &
\textbf{59.7} & \textbf{90.3} & 1.0 & 99.9 &
\textbf{62.4}\tabularnewline
Main source of water is basic drinking water** (Outcome 1) &
\textbf{77.4} & 97.2 & \textbf{68.9} & \textbf{55.0} & 90.5 & 99.6 &
\textbf{76.4}\tabularnewline
Main source of water is basic drinking water that is always available
(Outcome 2) & \textbf{35.0} & 92.3 & \textbf{41.5} & \textbf{46.9} & 1.0
& 99.6 & \textbf{45.7}\tabularnewline
Included in analysis & \textbf{Yes} & No & \textbf{Yes} & \textbf{Yes} &
No & No & \textbf{Yes}\tabularnewline
\bottomrule
\end{longtable}

\textbf{*Improved water sources include: Piped water, boreholes or
tubewells, protected dug wells, protected springs, rainwater, and
packaged or delivered water.}

\textbf{**Basic drinking water is defined as drinking water from an
improved source, where collection time is not more than 30 minutes.}

\textbf{***Sites were included in our analysis if they had sufficient
variability in the outcomes of interest (\emph{\textgreater{}}10\%
and\emph{\textless{}}90\% of observations with Outcome 1 or Outcome 2).}

\textbf{Table 2. Variables included in Random forests models}\selectlanguage{english}
\begin{longtable}[]{@{}llll@{}}
\toprule
Variables & Variable name in RF plot & Variable format &
Lag\tabularnewline
\midrule
\endhead
Rainfall variables & & &\tabularnewline
Mean two-week precipitation & biweekly\_p & Continuous &
0\tabularnewline
Mean four-week precipitation & fourweekly\_p & Continuous &
0\tabularnewline
Mean eight-week precipitation & eightweekly\_p & Continuous &
0\tabularnewline
Mean two-week precipitation, lagged one week & biweekp\_lag1 &
Continuous & 1 week\tabularnewline
Mean two-week precipitation, lagged two weeks & biweekp\_lag2 &
Continuous & 2 weeks\tabularnewline
Mean four-week precipitation, lagged one week & fourweekp\_lag1 &
Continuous & 1 week\tabularnewline
Mean four-week precipitation, lagged two weeks & fourweekp\_lag2 &
Continuous & 2 weeks\tabularnewline
Days since previous rainfall & preraindays & Continuous &
0\tabularnewline
Maximum one-day rainfall in previous two weeks & max\_2 & Continuous &
0\tabularnewline
Maximum one-day rainfall in previous four weeks & max\_4 & Continuous &
0\tabularnewline
Number of high precipitation days (over 95\textsuperscript{th}
percentile) in previous two weeks & sum\_high\_p & Continuous &
0\tabularnewline
Temperature Variables & & &\tabularnewline
Mean two-week temperature & biweekly\_t & Continuous & 0\tabularnewline
Mean four-week temperature & fourweekly\_t & Continuous &
0\tabularnewline
Mean two-week temperature, lagged one week & biweekt\_lag1 & Continuous
& 1 week\tabularnewline
Mean two-week temperature, lagged two weeks & biweekt\_lag2 & Continuous
& 2 weeks\tabularnewline
Mean four-week temperature, lagged one week & fourweekt\_lag1 &
Continuous & 1 week\tabularnewline
Mean four-week temperature, lagged two weeks & fourweekt\_lag2 &
Continuous & 2 weeks\tabularnewline
Number of high temperature days (over 95\textsuperscript{th} percentile)
in previous two weeks & sum\_high & Continuous & 0\tabularnewline
Number of low temperature days (below 5\textsuperscript{th} percentile)
in previous two weeks & sum\_low & Continuous & 0\tabularnewline
Other Variables & & &\tabularnewline
Case/Control status & Type & Dichotomous & N/A\tabularnewline
Maternal education level & educat & Categorical & N/A\tabularnewline
Socio-economic index & wealth & Continuous & N/A\tabularnewline
Month and year of observation & monthyear & Continuous &
N/A\tabularnewline
\bottomrule
\end{longtable}

\textbf{Figure 1. Main sources of water use by site. Sources in blue
indicate those categorized as an ``improved water source'' by the WHO.}\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image1/image1}

\end{center}
\end{figure}\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image2/image2}

\end{center}
\end{figure}

\textbf{Figure 2. Weekly temperature (red) and precipitation (blue) over
the study period, by site}

\textbf{Table 3. Top ten most important predictor variables of basic
drinking water use (outcome 1) and using basic drinking water that is
always available (outcome 2) identified using random forests models and
model parameters by site and outcome, dark red =
1\textsuperscript{st}most important, light yellow =
10\textsuperscript{th} most important.}\selectlanguage{english}
\begin{longtable}[]{@{}lllllllll@{}}
\toprule
Variable & The Gambia & The Gambia & Mozambique & Mozambique & Kenya &
Kenya & Pakistan & Pakistan\tabularnewline
\midrule
\endhead
Outcome Modeled & 1 & 2 & 1 & 2 & 1 & 2 & 1 & 2\tabularnewline
\textbf{Demographic Variables} & \textbf{Demographic Variables} &
\textbf{Demographic Variables} & \textbf{Demographic Variables} &
\textbf{Demographic Variables} & \textbf{Demographic Variables} &
\textbf{Demographic Variables} & \textbf{Demographic Variables} &
\textbf{Demographic Variables}\tabularnewline
Wealth & 1 & 1 & 1 & 1 & 1 & 1 & 1 & 1\tabularnewline
Maternal education & 2 & 7 & 2 & & 2 & 2 & 2 & 2\tabularnewline
Case/Control & & & & 2 & 4 & 3 & 9 & 8\tabularnewline
\textbf{Temperature Variables} & \textbf{Temperature Variables} &
\textbf{Temperature Variables} & \textbf{Temperature Variables} &
\textbf{Temperature Variables} & \textbf{Temperature Variables} &
\textbf{Temperature Variables} & \textbf{Temperature Variables} &
\textbf{Temperature Variables}\tabularnewline
Two-week temp & 5 & 2 & 8 & 8 & 6 & 7 & 4 & 3\tabularnewline
Two-week temp, lag1 & 3 & 3 & 9 & 3 & 8 & 9 & 5 & 4\tabularnewline
Two-week temp, lag2 & 4 & 4 & & 4 & 7 & 10 & 6 & 6\tabularnewline
Four-week temp & & 9 & & & & & 8 & 7\tabularnewline
Four-week temp, lag1 & 6 & 10 & 10 & & 9 & & 10 & 10\tabularnewline
Four-week temp, lag2 & 7 & 5 & 7 & 5 & 10 & 6 & 7 & 9\tabularnewline
\textbf{Precipitation Variables} & \textbf{Precipitation Variables} &
\textbf{Precipitation Variables} & \textbf{Precipitation Variables} &
\textbf{Precipitation Variables} & \textbf{Precipitation Variables} &
\textbf{Precipitation Variables} & \textbf{Precipitation Variables} &
\textbf{Precipitation Variables}\tabularnewline
Days since rainfall & 8 & 8 & 4 & & & & 3 & 5\tabularnewline
Two-week precip & & & & & & 5 & &\tabularnewline
Two-week precip, lag1 & 9 & 6 & 3 & 6 & & & &\tabularnewline
Two-week precip, lag2 & 10 & & 5 & & 5 & 4 & &\tabularnewline
Four-week precipitation & & & & 10 & & & &\tabularnewline
Four-week precip, lag1 & & & 6 & 7 & & & &\tabularnewline
Four-week precip, lag2 & & & & 9 & & 8 & &\tabularnewline
Eight-week precip & & & & & 3 & & &\tabularnewline
\textbf{Model Parameters} & \textbf{Model Parameters} & \textbf{Model
Parameters} & \textbf{Model Parameters} & \textbf{Model Parameters} &
\textbf{Model Parameters} & \textbf{Model Parameters} & \textbf{Model
Parameters} & \textbf{Model Parameters}\tabularnewline
Number of trees & 250 & 250 & 500 & 250 & 500 & 500 & 250 &
250\tabularnewline
Number of variables tried & 15 & 15 & 14 & 11 & 14 & 12 & 15 &
17\tabularnewline
OOB error (\%) & 4.55 & 11.86 & 8.68 & 10.21 & 16.93 & 19.18 & 7.29 &
17.82\tabularnewline
Validation error (\%) & 5.00 & 13.50 & 9.00 & 9.95 & 18.00 & 21.10 &
6.80 & 18.30\tabularnewline
\bottomrule
\end{longtable}

\textbf{Table 4. Magnitude and direction of associations between most
important variables from random forest analysis and basic drinking water
use (Outcome 1), adjusted for wealth, by site. Associations are odds
ratios and 95\% confidence intervals comparing the highest
quartile/category to the lowest quartile/category of each variable.
When, in tests for linearity, no difference was seen between adjacent
categories, quartiles were collapsed and we provide ORs comparing the
highest to lowest category (detailed descriptions of variable
specification are provided in supplemental tables 2 - 5). Colors
indicate direction and strength of association: red = decreased basic
drinking water use; blue = increased basic drinking water use. Grey
indicates association untested because the variable was not identified
as an important predictor in random forests. White cells indicate the
association was tested but was not statistically significant.}\selectlanguage{english}
\begin{longtable}[]{@{}lllll@{}}
\toprule
Variable & The Gambia & Mozambique & Kenya & Pakistan\tabularnewline
\midrule
\endhead
\textbf{Demographic Variables} & \textbf{Demographic Variables} &
\textbf{Demographic Variables} & \textbf{Demographic Variables} &
\textbf{Demographic Variables}\tabularnewline
Increasing wealth & 3.38 (2.43, 4.71) & 1.61 (1.28, 2.04) & 1.19 (1.01,
1.39) & 2.62 (2.03, 3.38)\tabularnewline
Maternal education* & & 1.67 (1.26, 2.21) & 2.90 (2.12, 3.97) & 1.68
(1.27, 2.23)\tabularnewline
Case (vs. control) & & & 0.74 (0.64, 0.85) &\tabularnewline
\textbf{Temperature Variables} & \textbf{Temperature Variables} &
\textbf{Temperature Variables} & \textbf{Temperature Variables} &
\textbf{Temperature Variables}\tabularnewline
Two-week temperature & & 0.77 (0.62, 0.96) & 0.49 (0.40, 0.59) & 0.72
(0.59, 0.89)\tabularnewline
Two-week temperature with 1-week lag & & & 0.65 (0.53, 0.79) & 0.66
(0.53, 0.81)\tabularnewline
Two-week temperature with 2-week lag & 1.51 (1.05, 2.19) & & 0.70 (0.58,
0.85) & 0.67 (0.54, 0.82)\tabularnewline
Four-week temperature & & & & 0.68 (0.55, 0.83)\tabularnewline
Four-week temperature with 1-week lag & & & 0.66 (0.57, 0.76) & 0.61
(0.49, 0.76)\tabularnewline
Four-week temperature with 2-week lag & & & 0.71 (0.61, 0.81) & 0.64
(0.51, 0.79)\tabularnewline
\textbf{Precipitation Variables} & \textbf{Precipitation Variables} &
\textbf{Precipitation Variables} & \textbf{Precipitation Variables} &
\textbf{Precipitation Variables}\tabularnewline
Previous days since rain & & & & 0.71 (0.56, 0.90)\tabularnewline
Two-week precipitation & & & &\tabularnewline
Two-week precipitation with 1-week lag & & & &\tabularnewline
Two-week precipitation with 2-week lag & & 1.36 (1.10, 1.68) & 2.59
(2.12, 3.15) &\tabularnewline
Four-week precipitation & & & &\tabularnewline
Four-week precipitation with 1-week lag & & 1.28 (1.03, 1.60) &
&\tabularnewline
Four-week precipitation with 2-week lag, & & & &\tabularnewline
Eight-week precipitation & & & ~3.95 (3.21, 4.86) &\tabularnewline
\bottomrule
\end{longtable}

*Maternal education was categorized, based on relevant schooling in each
region, in three categories in the Gambia, Mozambique and Kenya, and
four categories in Pakistan. Estimates compare the highest to lowest
maternal education group for each region. Details are provided in
Supplemental Tables 2-5.

\textbf{Table 5. Magnitude and direction of associations between most
important variables from random forest analysis and using basic drinking
water which is always available (Outcome 2), adjusted for wealth, by
site. Associations are odds ratios and 95\% confidence intervals
comparing the highest quartile/category to the lowest quartile/category
of each variable. When, in tests for linearity, no difference was seen
between adjacent categories, quartiles were collapsed and we provide ORs
comparing the highest to lowest category (detailed descriptions of
variable specification are provided in supplemental tables 6 - 9).
Colors indicate direction and strength of association: red = decreased
basic drinking water use; blue = increased basic drinking water use.
Grey indicates association untested because the variable was not
identified as an important predictor in random forests. White cells
indicate the association was tested but was not statistically
significant.}\selectlanguage{english}
\begin{longtable}[]{@{}lllll@{}}
\toprule
Variable & Gambia & Mozambique & Kenya & Pakistan\tabularnewline
\midrule
\endhead
\textbf{Demographic Variables} & \textbf{Demographic Variables} &
\textbf{Demographic Variables} & \textbf{Demographic Variables} &
\textbf{Demographic Variables}\tabularnewline
Increasing wealth & 0.46 (0.35, 0.62) & 2.24 (1.73, 2.89) & 1.24 (1.02,
1.50) & 1.84 (1.50, 2.26)\tabularnewline
Increasing education levels & 1.36 (1.05, 1.77) & & 2.48 (1.85, 3.32) &
1.38 (1.13, 1.70)\tabularnewline
Case (vs. control) & & 0.44 (0.36, 0.54) & 0.76 (0.66, 0.87) & 0.75
(0.65, 0.87)\tabularnewline
\textbf{Temperature Variables} & \textbf{Temperature Variables} &
\textbf{Temperature Variables} & \textbf{Temperature Variables} &
\textbf{Temperature Variables}\tabularnewline
Two-week temperature & 0.51 (0.36, 0.71) & 0.77 (0.60, 0.99) & 0.51
(0.42, 0.62) & 0.87 (0.73, 1.04)\tabularnewline
Two-week temperature with 1-week lag & 0.73 (0.52, 1.03) & 0.78 (0.60,
1.00) & 0.67 (0.59, 0.78) & 0.73 (0.63, 0.85)\tabularnewline
Two-week temperature with 2-week lag & 0.66 (0.47, 0.92) & 0.81 (0.68,
0.97) & 0.73 (0.60, 0.88) & 0.67 (0.54, 0.82)\tabularnewline
Four-week temperature & 0.76 (0.62, 0.93) & & & 0.73 (0.63,
0.85)\tabularnewline
Four-week temperature with 1-week lag & 0.79 (0.65, 0.96) & & & 0.69
(0.69, 0.80)\tabularnewline
Four-week temperature with 2-week lag & & & 0.68 (0.60, 0.79) & 0.68
(0.59, 0.79)\tabularnewline
\textbf{Precipitation Variables} & \textbf{Precipitation Variables} &
\textbf{Precipitation Variables} & \textbf{Precipitation Variables} &
\textbf{Precipitation Variables}\tabularnewline
Previous weeks since rain & & & & 0.72 (0.59, 0.88)\tabularnewline
Two-week precipitation & & & 2.77 (2.27, 3.37) &\tabularnewline
Two-week precipitation with 1-week lag & 0.75 (0.64, 0.88) & &
&\tabularnewline
Two-week precipitation with 2-week lag & & & 2.06 (1.70, 2.51)
&\tabularnewline
Four-week precipitation & & 0.74 (0.60, 0.91) & &\tabularnewline
Four-week precipitation with 1-week lag & & & &\tabularnewline
Four-week precipitation with 2-week lag & & 0.79 (0.64, 0.97) & 2.29
(1.88, 2.79) &\tabularnewline
Eight-week precipitation & & & &\tabularnewline
\bottomrule
\end{longtable}

* Grey indicates association untested because the variable was not
identified as an important predictor. White cells indicate the
association was tested but was not statistically significant.

** Previous weeks since rain recalculated from previous days since
rainfall used in RF model.

\textbf{Figure 3. Potential pathways by which temperature or rainfall
could impact availability and use of water sources}\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image10/image10}

\end{center}
\end{figure}

\textbf{Hosted file}

\verb`gems wsh weather supplemental material.docx`  available at \url{https://authorea.com/users/555135/articles/605897-the-association-between-rainfall-temperature-and-reported-drinking-water-source-a-multi-country-analysis}

\selectlanguage{english}
\FloatBarrier
\end{document}

