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Video 1.3: Forecasts of Coverage

Course video 6 of 39

Water Supply and Sanitation Policy in Developing Countries Part 1: Understanding Complex Problems

Université de Manchester

Our course explores what can be done to solve the complex problem that half a billion people worldwide do not have improved water supplies and two billion do not have improved sanitation. We look forward to you joining us. We want to help you develop the skills you need to address this major global challenge of the 21st century. Our course has informative video lectures and guest interviews with leading water policy scholars and practitioners. We will provide you with discussion forum topic prompts, which will invite you to engage with other learners from around the globe. Our MOOC will also ask you to attempt weekly quizzes and a challenging assignment that tackles a real water and sanitation problem in a difficult setting. Please watch this trailer: https://youtu.be/Q-HmaCZNd0k

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Enseigné par

Prof Dale Whittington
Professor
Dr Duncan Thomas
Lecturer

Transcription

In this video, I want to explore the question of where coverage is headed.

In terms of our conceptual framework, I want to examine the dynamic baseline.

What do we think will happen in the water

and sanitation sector if current population and economic trends continue?

The forecasts I'm going to show you are joint work with

Marc Jeuland and several other of my colleagues at UNC.

The reading for this lesson, is just been

published in POLS1 and you can access it there.

We're going to be looking at three questions.

First, how are the economic losses associated with water and sanitation,

have they changed at the global level from 1900 to 2050?

Are things getting better or are they getting worse?

Will economic growth solve WASH problems in the near or medium term?

And third, where should donors concentrate their efforts in this sector

given where coverage is headed, in terms of economic growth in population?

We use a simulation model to forecast coverage in the years ahead.

We need some kind of technique to do this.

And what we're going to use is a three equation simulation model.

In the first equation, piped water coverage is a function of national income.

In the second equation, wash related mortality is a function

of piped coverage, and in the third equation, we try to

estimate economic losses as a function of deaths, illnesses, and other costs

that households incur, from having poor water and sanitation conditions.

It's actually rather surprising, that this hasn't been done before.

But, what I'm going to to show you then, is a picture of where the

world's headed in terms of water and

sanitation coverage, and where problems will remain.

The data we're going to use to estimate

this simulation model are at the country level.

They're country level averages.

Now there are problems with using country

level averages, particularly for big countries like

China and India, which households are going to

have many different conditions in modern sanitation.

But, we're going to take an average of those conditions, for the whole country.

We also have con, variables for coverage, for piped water, and

sanitation services, from the JMP, from 1990 to 2008.

And, we have WASH-related mortality statistics

from 2004, from the World Health Organization.

In addition to these country level data we also are going to

use data on urbanization, world regions,

literacy, fertility, governance and some time trends.

We're also going to look to the literature to help us understand

the relationship between income and the value of a statistical life.

We need to do this in order to estimate economic losses associated

with poor water and sanitation conditions today and then on into the future.

So first I want to give you an overview

of some of the global data about these relationships.

So in this slide you see that there's a clear association

between development, or GDP per capita, and access to piped water supply.

As GDP per capita goes up, access to piped water

supply and coverage of piped water supply goes up dramatically.

This next slide shows you that there's a clear

association between WASH-related mortality and access to piped water supply.

Now it's important to think a bit about causal relationships

here, and we're not making any causal claims in this modeling.

In other words, we're only talking about an association between these variables.

Certainly the causation runs in both directions.

As people get richer, they have more money

to spend on piped water and sewer services.

On the other hand, as health gets better and they

have piped water and sanitation

conditions, this also supports economic growth.

So there's a dual relation that we're not trying to tease out in this model.

I'm going to show you the results of

the coverage forecast first for four countries.

Brazil, China, India, and Nigeria.

These are some of the largest countries, in terms of population in the developing

world, and some of the most interesting in terms of coverage statistics.

This next slide shows pipped water coverage, again in China,

India, Brazil and Nigeria from 1950 to 2050.

For a 100 year period, the shaded area in this

graph in the middle shows you where we have data.

So before 1990, we're actually backcasting coverage, and

then after 2010 we're forecasting coverage into the future.

These forecasts show that China and Brazil have been moving

to very high levels of coverage as economic growth proceeds.

This has happened over the last 20 years.

India and Nigeria show much lower levels of piped water

coverage, but India shows increasing coverage over the next few decades.

Nigeria looks much worse.

Again, this is coverage, and part of the reason that

Nigeria looks worse is that population is growing so rapidly.

So as, even though maybe more and more people are getting piped

water coverage, it's just barely keeping up in Nigeria with population growth.

This next slide shows WASH-related mortality

in China, India, Brazil, and Nigeria.

So what we've done here in this simulation is to translate

these forecasts of coverage into the, forecast of WASH-related mortality rates.

And in this next slide I'll show you WASH-related deaths.

So this slide shows WASH-related mortality rates.

And you can see in Brazil and

China WASH-related mortality has actually collapsed already.

WASH mortality rates in India are above

China and Brazil, but they're trending down, and

we expect from our forecast that they will

get, very low over the next couple decades.

Nigeria on the other hand, mortality rates are much higher.

They are trending down over the next few decades, but

they still remain in our forecast at quite high levels.

This next slide shows total WASH-related deaths, and which these are number

of people dying from WASH-related diseases in these four countries.

These are backcasts to 1900, and then forecasts from 1910 to 2050.

So as you can see the total number

of deaths in China probably peaked around 1980.

And these have essentially disappeared.

Similarly the number of WASH-related deaths in Brazil is now very low.

The number of deaths in India is much higher, but

is also trending strongly down over the next couple decades.

In Nigeria however the number of WASH-related

deaths, is actually forecasted to rise though the

forecast period, due to high population growth in

the low baseline levels of piped water coverage.

This next slide shows you total economic

losses in China, India, Brazil, and Nigeria.

Our estimates of total economic losses in monetary terms show even more dramatic

declines in China and India, and more dramatic increases in Nigeria.

The global projections by region are in your reading.

And I'm not going to go over them here, but they do look

similar to the projections for these four large countries in the developing world.

Let me conclude our discussion of coverage forecast with three observations.

First, economic growth will probably solve water and sanitation problems

in many parts of the world over the next couple decades.

For example, in East Asia, the East

Pacific, the Middle East and Latin America.

Second, the global community, international donors, and

NGOs should probably focus their efforts on

Sub-Saharan Africa and the rural parts of South Asia, such as the Ganges plain.

Third, there's nothing inevitable about these forecasts.

Policy interventions and deliberate actions can change them.

These are just trends in the dynamic baseline.

They're not inevitable.

So to wrap up this week, we've learned about

the spatial distribution of wash coverage statistics around the world.

And that they're big differences in WASH coverage between

urban and rural areas, and different regions in the world.

Next week we're going to continue our discussion

of the dynamic baseline and status quo

conditions by looking at water vending, and

corruption issues in the water and sanitation sector.

Don't forget to watch the video with Clarissa Brocklehurst

about the JMP coverage statistics, and how these were collected.

Thank you for watching the video this week.

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