Mathematical Modeling to Prioritize Water Interventions in - - PowerPoint PPT Presentation

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Aug 19, 2022 178 likes •359 views

Using Survey Data and Mathematical Modeling to Prioritize Water Interventions in Developing Countries Jane Cox, Konnor Petersen, and Jordan Spencer Dr. Tyler Jarvis https://math.byu.edu/waterdata Changing Charity with Data Maximize impact

SLIDE 1

Using Survey Data and Mathematical Modeling to Prioritize Water Interventions in Developing Countries

Jane Cox, Konnor Petersen, and Jordan Spencer

Dr. Tyler Jarvis

https://math.byu.edu/waterdata

SLIDE 2

Changing Charity with Data

Photo by dii9c from Pexels

Maximize impact
Optimize resources being used
Locate underserved areas

SLIDE 3

SLIDE 4

Water Interventions Tested

Chlorine Distribution
Dug Wells
Drilled Wells
Standpipes

SLIDE 5

Years Gained Cost

Capital Costs & Operational Maintenance Reduced Travel & Im Improved Health __________________

=

___________________

Model Breakdown

SLIDE 6

Data Source

Survey participants are

assigned to clusters

Cluster GPS Data is

connected to the 15-20 surveys

Individual location not given

due to privacy laws.

SLIDE 7

Cluster Boundaries: Voronoi Diagramming

Needed to know where

survey participants were located

Consistent and logical way

to divide the region

SLIDE 8

SLIDE 9

Estimating Household Locations

Need survey participant location

to calculate time saved when a new water source is introduced

Individual Geographical

information is not provided due to privacy laws

SLIDE 10

Household Sampling for Urban Clusters

Households are assumed to be

distributed uniformly across cluster

Optimal well is placed after

households to calculate new time spent gathering water

SLIDE 11

Household Sampling for Rural Clusters

Sampling is repeated

and time saved is averaged

Number of

population centers is random and uniformly distributed

SLIDE 12

Gamma Distribution

α (shape) and β (scale) are calculated using the mean and variance of given survey data

SLIDE 13

Years Gained Cost

Capital Costs & Operational Maintenance Reduced Travel & Im Improved Health __________________

=

___________________

Model Breakdown

SLIDE 14

Results: Namibia

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Results: Angola

SLIDE 16

Sensitivity Analysis

Derivatives of estimated variables were checked
Results were positive, variables with high sensitivity are reasonable

SLIDE 17

Changing Charity with Data

Photo by dii9c from Pexels

Maximize impact
Optimize resources being used
Locate underserved areas

SLIDE 18

Future Research:

Water table data in more accurately determining optimal intervention
Expand model to easily accommodate more countries
Utilize in real world application