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✇WASHeconomics Blog

Water supply & diarrhoea – latest systematic review and economic implications

By: IanRoss

An update to the WHO-led systematic review of the ‘Impact of drinking water, sanitation and handwashing with soap on childhood diarrhoeal disease’ by Wolf et al. (2018) was published in TMIH in May.

I re-read it last week with a water supply hat on, and was interested to see how they’ve improved on the 2014 version. The main difference, apart from including studies recently completed, is that they’ve updated the structure of the meta-regression to allow for separate results for “piped water, higher quality” and “continuous piped water”. This means there’s additional comparisons to be made (with more relevance for SDG6 “safely managed” definitions).

As background, their meta-regression approach allows estimation of service level transitions that have not been directly observed in studies. This builds on ‘network meta-analysis’, a technique increasingly being used in economic evaluations of health interventions where there are no head-to-head trials between options.

Below is my visualisation of the key results (building on the diagrams of the 2014 review’s results in this WHO publication). The numbers are percentage reductions in diarrhoea morbidity risk associated with each transition – explanation below the figure.

wolf et al* / ** see note at bottom of post

I made this based on table 3 of Wolf et al. 2018, calculating % reduction = 1 – risk ratio. In my view, the transitions most likely to happen in practice, as a result of investments, are the incremental ones. Therefore, I have put these in bold blue. Those transitions less likely are in bold back, and those fairly unlikely are in italics. By “unlikely”, I mean that those people remaining with unimproved water are now predominantly in rural areas, where the direct transition to a safely managed water supply (meeting SDG criteria for both quality and continuity) is unlikely to be affordable in many settings. This reduction (75%), which the authors estimated indirectly, would appear to be the reduction maximally achievable with water supply. Some more notes are at the bottom of this post.

What should we make of these results? I would make two observations, and then two arguments based on the economic implications.

  1. There is good evidence that improving people’s water supplies can reduce diarrhoea, which is among the top three contributors to the all-age disease burden amongst the two quintiles of countries with the lowest human development. For the transitions in the figure previously reported in the 2014 review, the only change is that the point estimate for improved off-plot to piped on-plot has fallen from 14% to 13%.
  2. The reduction varies by level of service attained. Piped water reduces diarrhoeal morbidity more than off-plot supplies, when provided at high quality and continuity. The continuity effect most likely happens via a direct increase in quality, though also via the fact that people are less likely to use secondary sources and improper storage.

What does this mean for the economics of water supply provision, specifically the comparison of investment options?

  1. There is an equity/efficiency trade-off to be made in investment prioritisation. Improving water quality in existing piped supplies has the largest single incremental effect (68%), and there are hundreds of millions of people in urban areas of developing countries using piped services which are not safely managed. Investments in this area are therefore important. However, any improvement in service level for populations using unimproved supplies should arguably be the highest priority on equity grounds, even if to an improved off-plot supply which has only an 11% reduction. Firstly, these populations are most likely to concentrated in rural areas where mortality risk from diarrhoea is highest. Furthermore, in such populations the 11% reduction is likely to be applied to a number of annual diarrhoea cases per capita which is higher than in most urban areas, where people also live closer to health services. Decisions obviously also take place not only on the effects side of the equation, but the cost side too.
  2. Broader benefits should also be taken into consideration. Time savings are often associated with a move from unimproved to off-plot improved supplies (and again in a move from there to on-plot piped). These have an economic value. Water quantity increases associated with a move to on-plot supplies decrease the opportunity cost of using water for handwashing, meaning it is more likely to happen. While improved continuity has a much smaller incremental impact (17%) than improved water quality (68%), improvements in continuity reduce wasted time and money invested in coping strategies and the use of secondary sources. These results are also based on a small number of studies (see below). In short, any decision should be based on a lot more than relative risk reductions.

Decision-makers are rarely faced with simple choices of ‘urban versus rural’, ‘pipes versus handpumps’, or ‘quality versus continuity’. The factors above are all built into the calculus of local government agencies and Ministries of Water when they make their investment plans. I would argue that the principle of “first a basic service for all” should be factored into any such decisions.

Notes

  • The bold blue figures are the ones for which we have studies with a direct comparison (though studies also exist comparing unimproved and piped) – see table 2 in the paper.
  • The asterisks denote that transitions to “piped, higher quality” rely on one study, and to “continuous supply” on two studies (against 6, 7 and 11 studies for other key transitions). So, these should be interpreted with caution.
  • I left out the results for point-of-use filters with safe storage to avoid cluttering the diagram, but the reductions for these are 48% (on an unimproved source). POU chlorination has limited impact after blinding is accounted for.
  • These are point estimates. Some of the upper bound 95% confidence intervals for risk ratios in table 3 are higher than 1, i.e. the result is not statistically significant.

washeconomics

wolf et al

✇ICT4WASH

First ICT4WASH Newsletter, and Course Announcement!

First ICT4WASH Newsletter, and Course Announcement!
View this email in your browser
Levyne Otieno installs a solar-powered wireless data logger that transmits water flow information to the utility.

Welcome to the first ICT4WASH Newsletter!


Dear ICT4WASH Members and Friends,

ICT4WASH is a community of individuals and organizations interested in the application of technology in the water, sanitation and hygiene sector.  The community emerged from a group of like-minded individuals interested in expanding international cooperation and capacity building around ICT in water and sanitation related activities, strategies and programs.

Members of the community connect, share, collaborate and learn through online and in-person networking and training workshops and events.

This newsletter will come out on occasion to share announcements on these activities, updates on member projects and initiatives, funding opportunities, and recent articles and publications of interest to the community.

If you would like to share news or resources with the rest of the community, simply reply to this email or forward them to info@ict4wash.com, and we’ll feature them in the next newsletter.

Also, don’t forget to join our Facebook group, and follow us on Twitter!

A cyble sensor sends meter readings to the data logger above for wireless data transmission.

Course Announcement!

ICT4WASH102 is a highly-interactive one-month eLearning course on ICT for Water Service Providers and other WASH sector stakeholders.

The course first launched in mid-2017 with 4 facilitators, 9 guest experts, and 50 participants from 16 countries.  With such positive results, organizers decided to run the course again from November 6 – December 1 with new guest experts and participants from around the world!

Managers and staff of Water Service Providers (WSPs), humanitarian organizations, non-profits, NGOs, government, and the private sector are invited to join the course which includes dynamic self-guided content, case studies, discussion forums, technology demos and practical exercises.  Participants test and use (and even develop!) mobile and web-based solutions, including mobile data collection apps, cloud-based databases, and custom and off-the-shelf mobile and geospatial solutions available on the market.

The course also features live and interactive guest expert presentations and Q&As with leading water and sanitation specialists, researchers, and ICT solutions providers.

Please share the news with colleagues and friends who might be interested!

ICT4WASH102 Course Page!
Recent Articles and Publications
 
ICT antiques at the University of Cape Town Centre in ICT for Development
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✇ICT4WASH

First ICT4WASH Newsletter, and Course Announcement!

First ICT4WASH Newsletter, and Course Announcement!
View this email in your browser
Levyne Otieno installs a solar-powered wireless data logger that transmits water flow information to the utility.

Welcome to the first ICT4WASH Newsletter!


Dear ICT4WASH Members and Friends,

ICT4WASH is a community of individuals and organizations interested in the application of technology in the water, sanitation and hygiene sector.  The community emerged from a group of like-minded individuals interested in expanding international cooperation and capacity building around ICT in water and sanitation related activities, strategies and programs.

Members of the community connect, share, collaborate and learn through online and in-person networking and training workshops and events.

This newsletter will come out on occasion to share announcements on these activities, updates on member projects and initiatives, funding opportunities, and recent articles and publications of interest to the community.

If you would like to share news or resources with the rest of the community, simply reply to this email or forward them to info@ict4wash.com, and we’ll feature them in the next newsletter.

Also, don’t forget to join our Facebook group, and follow us on Twitter!

A cyble sensor sends meter readings to the data logger above for wireless data transmission.

Course Announcement!

ICT4WASH102 is a highly-interactive one-month eLearning course on ICT for Water Service Providers and other WASH sector stakeholders.

The course first launched in mid-2017 with 4 facilitators, 9 guest experts, and 50 participants from 16 countries.  With such positive results, organizers decided to run the course again from November 6 – December 1 with new guest experts and participants from around the world!

Managers and staff of Water Service Providers (WSPs), humanitarian organizations, non-profits, NGOs, government, and the private sector are invited to join the course which includes dynamic self-guided content, case studies, discussion forums, technology demos and practical exercises.  Participants test and use (and even develop!) mobile and web-based solutions, including mobile data collection apps, cloud-based databases, and custom and off-the-shelf mobile and geospatial solutions available on the market.

The course also features live and interactive guest expert presentations and Q&As with leading water and sanitation specialists, researchers, and ICT solutions providers.

Please share the news with colleagues and friends who might be interested!

ICT4WASH102 Course Page!
Recent Articles and Publications
 
ICT antiques at the University of Cape Town Centre in ICT for Development
Join the ICT4WASH Facebook group, or follow us on Twitter by clicking the links below!
Copyright © *2017* ICT4WASH, All rights reserved.

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✇ICT4WASH

📢 ICT4WASH102 eLearning Course Application Deadline Tomorrow! 🎓⌛

📢 ICT4WASH102 eLearning Course Application Deadline Tomorrow! 🎓⌛
View this email in your browser

ICT4WASH102 Deadline Reminder!

 

Hi ICT4WASH Folks!

This is a friendly reminder that the deadline to apply for ICT4WASH102: ICT for Water Service Providers has been extended to tomorrow (Tuesday, October 31st).  The one-month course will run from November 6th through December 1st. 

ICT4WASH102 is a highly-interactive online eLearning course on how ICT (mobiles, IoT/M2M, smart metering, GIS, mobile payments, etc.) can be harnessed to reduce non-revenue water (NRW), and improve services provision, customer satisfaction, revenue collection, finances, and asset management.

Managers and staff from utilities, humanitarian organizations, non-profits, NGOs, government, and the private sector are all welcome to apply!

So far we have participants from Tanzania, Philippines, Zambia, Bangladesh, Canada, Kenya, Niger, Cambodia, India, United States, Malawi, Mali, Yemen, United Kingdom, Colombia, Nigeria, and Sierra Leone!


Invitations will be sent out by the end of the week, and selected participants will be able to enter the platform for Orientation to start a fun mobile data collection activity and scavenger hunt.

The application only takes a minute and can be done here:

ICT4WASH102 Course Application

 


If you would like to subscribe to the ICT4WASH Newsletter, click here to sign up, or navigate here:

http://eepurl.com/c66vj1

To include your ICT-related project updates, articles, publications, events, or other news in our next newsletter, please send them to:

info@ict4wash.com


 
Join the ICT4WASH Facebook group, or follow us on Twitter by clicking the links below!
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✇WASHeconomics Blog

What do we know about urban sanitation costs? (a review of Daudey, 2017)

By: IanRoss

A review paper (open access) on the costs of urban sanitation came out last year. Authored by Loïc Daudey (now of AFD but then a consultant for WSUP) it surveys the literature on lifecycle costs of full chain chain systems in Africa and Asia. I found it very useful for my purposes so thought I’d write a quick review.

The paper focuses on cost *ratios* between different sanitation systems analysed within the same study.  It’s a smart approach which avoids the pitfalls of comparing absolute costs across diverse contexts, which rarely sheds much light on things as there are so many determinants of costs. That’s the useful thing about one paper it reviews, Dodane et al. (2012) – also open access and the best study in this field – which compares a sewerage system to an FSM system in Dakar, Senegal. Crucially, the comparison is an area of the city where both are operating, thereby minimising contextual effects. More on that paper another time.

Daudey’s lit. review finds that conventional sewer systems are the most expensive solution, followed by a tie between ‘septic tank & FSM’ solutions and simplified sewerage, and finally various ‘pit & FSM’ solutions. He concludes that ST & FSM comes out more expensive than simplified sewerage, but that doesn’t seem to be supported by the results. See below the key figure with some annotations of my own, including red boxes to emphasise where the median is (the black dashes), and some analysis. It’s a neat way to present the results – each stack of datapoints is the ratio between the first and second technology type in the respective X-axis label. My beef with the conclusion above is that since the median for ‘ST & FSM’ versus ‘simplified sewer’ is more or less 1, that means there’s little between them. Sure, the mean would be higher due to the outlier where the ratio is 4, but arguably the median is a better measure of central tendency for this kind of data.

Daudey1

Another key point stands out of the figure – there is a huge range of cost ratios for conventional sewerage vs ST & FSM – seven datapoints ranging from 1:1 up to almost 5:1. That rams the point home that context matters – sewerage is often but not always more expensive. Daudey has a nice table on cost determinants – my impression from working in a few cities and talking to engineers is that population density and topography are likely to be the most important, but I’m not aware of research that has gone into depth on this (please msg me if you know of any!).

I think the policy Q here is a three-way debate between conventional sewerage V simplified sewerage V ST & FSM. Yes pit latrines are important in many places and will continue to be important (especially in places with limited water for flushing), but few cities will be prioritising them for expansion in master plans. So, as I argued in this other blog , while conventional and simplified sewerage need to be a big part of the picture, the population numbers mean that FSM-based solutions will be with us for some time. And what Daudey’s review shows is that we shouldn’t necessarily be under the impression that FSM-based solutions are always cheaper than sewerage. Context is key.

Finally, then, a bit of the critique of the paper (other than the point above that one key conclusion is weakly supported by the findings).

1.He could have applied a more structured approach to study quality ratings. This is  common in systematic reviews, see e..g. Appendix S5 of this key WASH/diarrhoea review (Wolf et al 2014). The rating process is implicit rather than explicit – maybe it would have been better to score studies and only including the very strongest in a sub-set of ratio analysis, or maybe colour-code the strongest studies in the figure above.

2. Related to that, the review process could have been made more transparent through using something like a PRISMA diagram. It’s fine in many circumstances not to actually do a systematic review, but it’s not hard to be transparent about what was actually done (which still may be very systematic). Stick it in “supplementary material” if you don’t have the space.

3. There could have been more detailed examples relating to the key findings, (e.g. the life-cycle cost ratios) and relegated to “supplementary material” some of the stuff that was inconclusive e.g. on OpEx.

4. He could have contacted some of the authors of studies when things weren’t clear. There is some valid criticism in the paper of a study I was involved in in Dhaka, Bangladesh, but that was a wide-ranging 120pp report and we only had space for 6pp on the costing part (with some huge caveats on data quality) . There is loads of underlying material and we could have answered some of his Qs if he’d emailed us. The same is probably true for other studies where it’s said that things aren’t clear.

5. Minor point, but there could been more on the effects side. Sure, that was outside the scope of the paper to address it in detail. But considering costs on their own isn’t necessarily that illuminating for a decision-maker. Some of these service levels are associated with different disease effects, and different non-health benefits to households and different types of public goods. There could have been a bit more emphasis on how the effects side should be a key part of any decision.

Notwithstanding all these points, I found it a very useful paper that I’ll surely be dipping in and out of in the next few years as I try to move forward some work on urban sanitation costs myself.

Overall, then, what do we know about urban sanitation costs? My answer would be “not enough”. Luckily, there are plenty of people now working on this. Leeds are doing their CACTUS project, and WSUP are about to contract some consultants to do some work on costing and willingness to payAguatuya are also reportedly working on some kind of tool. So fingers crossed that in a couple of years time we’ll know a lot more! I’ll aim to write another blog in a few weeks about how we can better capture cost data that organisations are generating anyway, without much additional effort.

 

 

washeconomics

Daudey1

✇WASHeconomics Blog

Determinants of urban sanitation costs – ‘willingness to connect’ and scale effects

By: IanRoss

The Daudey 2017 paper (open access) I reviewed in this post has a useful table (p.7) of 9  determinants of urban sanitation costs. I would tend to group them more simply into three headings as below – I won’t go into these more here as the table in the paper is good.

1. Technology: technology type, level of service (e.g. shared or not)

2. Input prices: labour, materials, energy,

3. Geography: population density, topography, soil condition, distance to treatment

However, I would also add a fourth set of determinants which Daudey doesn’t include (or are implicit), namely broader economic ones. Each in turn is discussed in this blog.

4. Economics. willingness and ability to pay, macroeconomy and business envt.

For sewer networks in particular, an oft-forgotten determinant of medium- to long-term per capita costs is willingness and ability to pay. Or rather, willingness to connect. I underline per capita above because many networks operate below capacity, spreading fixed costs of trunk lines and treatment plants over a smaller number of connections than initially planned. Even though the overall CapEx doesn’t change much, the cost per capita is driven up by the fact that there are fewer users (capita…).

This is demonstrated in several of Guy Hutton’s East Asia studies under the Economics of Sanitation Initiative. For example, in their Cambodian study, only about 20% of targeted households were actually connected to the sewerage system. This meant that while the “ideal” scenario had a cost per private latrine with sewer connection was US$ 5,263, in the “actual” scenario it was US$ 17,537 at the current connection rate. This ‘willingness to connect’ issue is something the World Bank have explored elsewhere – see here.

Willingness to connect could either stem from (i) people possibly being keen to connect but not affording the connection fee (ability to pay, ATP), or (ii) able to pay but still not wanting to connect as they don’t perceive the benefits (to them as a private citizen) to be greater than costs (willingness to pay, WTP). In most cases, social benefits from a sewer system should be greater than social costs if everyone connects, or the system would have been unlikely to be approved.*

In theory this problem of higher than expected per capita costs happens with non-networked systems. However, the key difference is that they are more easily scaled up or down. Here’s an FSM example, quite basic, to keep things simple – market failures mean it is unlikely to happen quite this way in reality: Emptying services are privately provided and the market supplies Y vacuum trucks if demand is presently X. When demand rises to 2X (and this is perceived to be stable), providers are incentivised by rising prices (invisible hand etc.) and will accordingly invest in more trucks. Supply then  rises to 2Y or similar. While excess capacity is still possible, it is less likely to occur than with a sewer system that must necessarily be designed for the maximum connected population expected within a 20-30 year time horizon, i.e, some anticipated demand of anything between 10X-40X. A related aspect is that the FSM system is that isolated failure of components may not have big repercussions – e.g. a vacuum truck being out of service reduces FSM service supply marginally, whereas a pumping station being out of service can reduce sewerage services dramatically.

However, an FSM-based system clearly still has the same scale / time horizon issue for the treatment part of the chain – i.e. you need to design a FSTP for maximum projected demand. So,  there may well be excess capacity there in the short-to-medium-term. But that does not matter as much if it is a simple treatment technology with low running costs, as compared to a sewer system which requires a minimum of energy to run at all, regardless of wastewater volumes.

Considering the second part of my #4 bullet back at the start, the macroeconomic situation and business environment can be seen as more distal determinants of the input prices under #2. This is nicely demonstrated by EAWAG’s report on costing on-site sanitation – Ulrich et al 2016 – which includes a useful figure (pasted below) on ‘cost factors’ (ovals in the below) and how these influence material and labour costs.

Prices of materials are determined by many things, including taxes, exchange rates, trade barriers, competition, regulation etc. and the broader “business environment”. For example, if a land-locked country is importing key materials and customs/ports are inefficient, that will drive up costs. Some of this is implicit in Daudey’s table under input prices. Likewise for labour prices, the competitiveness of the broader labour market, and associated regulation, will strongly determine labour costs. So will other macro-economic factors like unemployment (not straightforward in LMICs) and inflation.

In conclusion, many, many factors determine per capita costs of urban sanitation. This is why it is quite hard to compare costs across countries. Other sectors such as health also face this issue. Accordingly, systematic reviews of economic evaluations in health tend to tabulate and compare results, stating contextual factors, rather than doing a meta-analysis (as would be done for health interventions where a more uniform estimate might be expected across contexts).

ulrich_determinants

 

*This disconnect between private and social benefits occurs because sanitation has public good characteristics. If discharging fecal waste untreated incurs no costs/fines (as is the case in Dhaka for example, where most septic tanks discharge direct to drains), then society pays for the consequences of that  negative externality.

washeconomics

ulrich_determinants

✇ICT4WASH

💧 ICT4WASH Newsletter, and New Course Announcement! 📢

💧 ICT4WASH Newsletter, and New Course Announcement! 📢
View this email in your browser
Communications.  The 'C' in 'ICT4WASH'.  This low-cost wireless access point creates a local hotspot, and communicates with antennas that transmit a wifi signal over long distances.  This creates a wireless mesh network which can be used for both communications and monitoring of services.

Welcome to the first ICT4WASH Newsletter of 2018!


The ICT4WASH Community emerged in 2017 as a platform for international cooperation and capacity-building between water and sanitation-related organizations and individuals in over 18 countries.  

Since then we have developed online eLearning courses, a newsletter, facebook group and have over 1100 people in our network from 34 countries

Many have reached out to with us with fantastic ideas on what ICT4WASH should offer in the coming year and beyond. More courses, more discussions and webinars, more information on ICT-related projects around the world....

Do you have 2 minutes to give us your thoughts as well? If so, please fill out this quick (seriously, very quick) survey!!!

Best Regards,

The ICT4WASH Team

2-Minute ICT4WASH Survey
Here a utility field team receives the daily list of repairs to be done from the Technical Manager.  The jobs are marked as complete throughout the day, and updated on an online dashboard.

New Course Announcement!

We are very excited to announce the launch of the brand new course:
 

 ICT4WASH310 - Mobile Money Payments for Utility Service Providers

The GSMA and Wakoma Incorporated have teamed up to develop this 3-week eLearning course based on the GSMA's Mobile Money Payment Toolkit.

Course Dates: April 9th-27th

This course was built to support utility service providers in deploying mobile money payment solutions.  It provides guidance on key questions around implementation of a mobile money platform, including when and how to approach integration, making the business case, as well as general considerations around legal requirements, customer experience and education.

All case studies, research and funding for the development and implementation of this course were provided by the GSMA. The course is free to attend for all participants.

Click the button below to apply for a spot while there's still space!

Apply Here!
Recent and relevant articles, publications, reports:
Here is a list of recent resources and webinar recordings organized by RWSN partners (sent from Sean Furey):
Please remember that if you would like to share news or resources with the rest of the community, simply reply to this email or forward them to info@ict4wash.com, and we’ll feature them in the next newsletter. You can also post them on the ICT4WASH Facebook group!
An ICT graveyard at a utility that has swapped out dataloggers for cheaper mobile phones with far more functionality.

A listing of 2018 WASH conferences, from Dan Campbell at the USAID Water Team:


MARCH

APRIL

MAY

  • May 28 – Menstrual Hygiene Day – Menstrual Hygiene Day (MH Day) is a global platform that brings together non-profits, government agencies, the private sector, the media and individuals to promote Menstrual Hygiene Management (MHM).

JULY

AUGUST

OCTOBER

NOVEMBER

Join our ICT4WASH Facebook group, follow us on Twitter or check out the course catalog!:
Sign up for this newsletter here
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✇WASHeconomics Blog

Incremental benefits from increases in sanitation service level

By: IanRoss

The Indus valley civilisation (c.2,000 BCE) coupled on-plot water supply from wells with the first known sewers. However, it was the Minoans (also c.2,000 BCE) who were the first to have piped water systems – I marvelled at the clay pipes and stone sewers at Knossos on Crete. The Minoans understood that piped water on demand provided a better service than carrying it in jars. Their piped systems are likely to have cost more than alternatives, especially in a slave-owning society where labour was “cheap”/free. But the richer households of Knossos were willing to pay for that higher level of service.

Turning to modern day sanitation, a high level of service such as a sewer connection is going to cost more than an unimproved pit latrine, but also provide more benefits. By extension, each movement up the rungs of the sanitation ladder has incremental costs and incremental benefits. Note that ‘incremental’ is different from ‘marginal’ – in welfare economics marginal benefit is strictly speaking the additional satisfaction or “utility” we receive from an additional unit of a good or service (e.g. from an additional litre of water). Incremental benefit, however, can refer to any change in the output of interest.

It was thinking about this, and playing with the cost data in Hutton & Varughese’s 2016 report on SDG costs, which led me to produce the below chart. It aims to visualise which incremental benefits are associated with the incremental cost of an increase in sanitation service level. For example, the movement from open defecation to a private but unimproved pit latrine is associated with time savings and ideally some privacy and security too (depending on the superstructure). This movement has a fairly small annualised life-cycle cost per household, which is even lower if the latrine is shared with other households. Achieving such a service level increase might be the objective of many CLTS programmes.

The bars are ‘annualised life-cycle costs per household’ of that option (comprising hardware/software CapEx, OpEx and CapManEx). The coloured text qualitatively describes possible incremental benefits of moving up to that rung on the ladder, from the previous.

Figure 1: Incremental benefits of moving up the sanitation ladder, alongside costs of different levels of sanitation service (average for Sub-Saharan Africa)

costs_per_service_level

A similar logic applies to the other increases in service level. Moving from an unimproved pit to an improved-but-shared system (“limited” in SDG terms) can bring health benefits in the right circumstances, as well as some ‘wellbeing benefits beyond health’ such as privacy, dignity, security and comfort. However, many factors will determine whether these benefits are realised, including consistency of use, cleanliness of the facility, the sanitation practices of the rest of the community, and many more. For the move to ‘basic’ services, there is evidence for higher benefits over ‘limited’ services but it is mixed – no space to go into that here. Finally, the move to safely managed services (whether non-networked with FSM or networked sewerage) is where significant health benefits community-wide should be seen, through the removal of negative externalities once a high enough proportion of people are at that service level.

The cost data comes from Hutton & Varughese 2016 – the World Bank has helpfully published the dataset here. I used their raw data for urban areas for four technology options, reported in annualised per capita life-cycle costs: (i) cost of any pit latrine, (ii) cost of a septic tank system, (iii) incremental cost of septic tank system with FSM, and (iv) incremental cost of sewerage with treatment. Since the latter two are incremental costs, I added them to the cost of a septic system to get the total cost. I calculated the average for Sub-Saharan African countries, and then used assumptions as follows: I assumed a household size of 5 to get to per household costs, and an assumption of 3 households sharing to get to the shared estimates. Finally, an unimproved pit was assumed to cost 25% of an improved pit.

The figure above represents a simplification of reality, since all benefits rely on contextual factors – note the ‘likelihood’ framing in the figure. Around 1,000 people building and using improved pit latrines is likely to have a bigger health effect in a village of 1,200 people than in a city of 1 million, depending on the baseline situation. Similarly, a new borehole is likely to  have more benefits in a village where everybody drinks from the river, than in a village where most people already have piped water.

Furthermore, there are other economic benefits from different levels of service, such as avoided healthcare costs and time wasted in sickness or caregiving, or the potential value of resource reuse. Nonetheless, I think the figure represents a useful way to think about what we get for our money when we invest in higher levels of service.

Has someone else visualised incremental costs/benefits before, like this or in a different way (I couldn’t find anything)?

What would you improve about the figure? Do comment below.

 

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costs_per_service_level

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Sanitation’s share of water sector aid is falling

By: IanRoss

I went to an interesting event at LSHTM last night run by Countdown 2030, on tracking aid flows to track global aid flows to reproductive, maternal, newborn and child health (RMNCH). Their dataset is here. Yet another reminder that the health sector is way ahead of the WASH sector on so many analytical questions, but also that they face many of the same problems.

For example, the four (!) different methods for tracking RMNCH flows all use, at best, the “long description” on the OECD’s creditor reporting system (CRS), in which donors report aid flows. In my experience these can often have as illuminating descriptions as “the WASH project”, even for multi-million dollar disbursements. Delving deeper into project documents underlying the headline figures, in order to allocate between sub-sectors / areas, is only possible for national-level analyses, and is tedious and hard to automate.

Last night’s event took me back to work I did at WaterAid in 2008 as part of advocacy towards establishing what is now Sanitation and Water for All (SWA). At that time, I became rather too acquainted with the CRS, being the lowly RA crunching the numbers for this report. Many of our observations still stand for WASH, but also for RMNCH. It was depressing to hear research presented last night that showed aid effectiveness has actually gone backwards on many counts since 2010/11. Five countries had >30 donors providing aid to RMNCH – such fragmentation involves huge duplication and unnecessary administration for government ministries.

Going back to WASH, at that time of our 2008 analysis, the OECD didn’t have separate reporting codes for sanitation and water, so it was not possible to see what was going on for sanitation specifically. One results of the advocacy around SWA and the “international year of sanitation” that year was that the OECD instituted separate codes for reporting from 2010 onwards.

So, on the bus journey back to Oxford I decided to check back what had happened since, within the water sector as a whole. See the graph below, which necessitated a few methods assumptions summarised below this post. For transparency, here’s the XLS. The results show that the overall share of water sector aid allocated to sanitation has been slowly and steadily falling over the past 5-6 years, while that for water supply has been increasing.

washaid

Other categories have stayed more or less the same. Sanitation’s share has been falling from around the high 20s in 2011 to the low 20s in 2016. It would take some more detailed analysis to look at what is causing this (which donors, which recipients). I did google for this analysis but nobody seems to have done it that I can find (though see re: GLAAS below) – if I missed something, please point it out in the comments.

Note that this is in constant US$ / real terms, i.e. inflation is accounted for in the figures, and that these are disbursement data from all donors to “developing countries” as defined by the OECD. They are also for ODA, so excludes anything that isn’t within the DAC definition (e.g. Gates foundation, which is sizeable).

The 2017 GLAAS report (p.30) has a figure related to this, pasted below. The right-hand panel has a 65/35 split between water/sanitation (when I do the 2015 split for the sanitation and water codes I get 68/32, a minor niggle probably resulting from which donors they included or some minor methods difference). GLAAS 2017 was on financing, so also has a lot more analysis on different aspects of aid flows and government WASH funding. I would argue that it’s only when more countries are producing National WASH Accounts, using the TrackFin methodology or similar, that we’re really going to know what’s going on with financial flows at the national level, from all sources, which is far more important.

glaas_san_aid

In conclusion, the fact that sanitation’s share of water sector ODA is falling should be cause for concern. We don’t want the momentum built up after the international year of sanitation to be lost. Someone with more time than me should look into what’s behind this trend, and which donors/recipients are driving it, so that advocates can try to ensure that the share doesn’t fall further.
Methods points:

DAC purpose codes for 2016 are here. In the figure, the “WASH” category up to 2009 comprises six codes: two which are WASH combined (‘WASH – large systems’, ‘WASH – basic’,) and four which are separated by sector (‘Water – large systems’, ‘Sanitation – large systems’, ‘Water – basic’ and ‘Sanitation – basic’). Under “WRM” I grouped the codes for water resources conservation and river basin development. “Other” comprises codes for waste management and WASH education & training.

The key assumption is as follows: up to 2009, all water supply and sanitation aid is grouped under WASH (grey in the figure). From 2010 I used the newly-disaggregated codes to separate out sanitation (light blue) from water (yellow). However, even in 2016 there was still more aid under the combined WASH codes than under the separate sanitation and water codes. So the key assumption is that, where data are disaggregated between sanitation and water, the proportion of those values in that year can be applied to the WASH codes which are not disaggregated.

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glaas_san_aid

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Categorisation of shared sanitation – some city-wide data using one approach

By: IanRoss

There has been a fair amount of debate on the role of shared sanitation in urban settings recently, see e.g. this comment piece from various stakeholders, this paper (plus others) from Sheillah Simiyu and this one from Marieke Heijnen. Also, WSUP recently issued an RFP for multi-country research on shared sanitation. In my own little corner of the sector, I’m working on a costing and cost-effectiveness study of the WSUP shared sanitation intervention in Maputo.

There are many types of shared sanitation – a toilet (or toilet block) can be shared amongst 2-3 families on a compound, among 20-30 identified families in a small area, or among all-comers willing to pay the entrance fee per use. A few years ago Adrien Mazeau did some work on ways of categorising the many different ways we can cut shared sanitation, ending up with a detailed typology (p.23). The categorisations are by location, access to whom, relationship of users, ownership, management, operation and payments.

A recent conversation on this issue made me look back at the data we collected under the World Bank five-city FSM study in 2014-16 (summary report here). Some useful data tables didn’t make it into the city reports (they were already 120pp long…). Below is a graph that didn’t make the cut. It shows sample survey data which are city-wide representative, collected in 2014-15 – more on the sampling in each city report. The variable shown is the latrine “usually used”, based on a simple sharing typology more or less the same as that suggested by the 2017 editorial referenced above:

  1. Household private (on-plot)
  2. Household shared (on-plot)
  3. Communal – pay per period (off-plot)
  4. Public – pay per use (off-plot)

Therefore, this sets aside issues of improved/unimproved (let alone safely managed), to zoom in on whether the toilet is on/off plot and the payment arrangement.

santype5city

* In Dhaka, there is also data representative of ‘slum’ areas (as defined by the Bangladesh Centre of Urban Studies). All information on sampling is in the city reports.

In the city-wide data, the graph shows that private household sanitation is used by the majority of households across these cities, with a sizeable proportion also using on-plot household shared. Only in Hawassa, Ethiopia, does communal sanitation play a role, for around 6% of households. In the data for low-income areas, it is clear that sharing plays a far larger role. In the Dhaka slums, less than 20% have private household toilet, and communal sanitation comprises almost 40% of toilet use. Pay-per-use public toilets were almost never used as the primary sanitation option in these cities, but this does not mean they don’t play an important role in providing sanitation options when people are out and about. nb. there was no open defecation reported as primary option in any city.

These categories were not derived from a single household survey question, but a series of questions about the attributes of the categories (questionnaire here). The difference between “household shared” and “communal” is that the former involves households sharing a toilet on their plot, with whatever cost-sharing arrangement they decide together, if any. The latter is normally a bigger “toilet block” type of arrangement where households can pay per month or similar for access whenever needed, and they have to leave their plot to get there (see this paper). Public toilets can be used by anyone, either for a small fee for each use or for free.

I’m not suggesting that the above categories are the best way to go. More work is needed on which categorisations are most important for policy/planning. Definitely it will be more than one set, as you can’t get all the relevant information (imp./unimp., on/off-plot, who can access, payment etc.) into one variable without it becoming unmanageable. The ways in which we categorise sanitation options and frame household survey questions and response categories are crucial for a good understanding of what is going on. Any given study or monitoring regime will have its own priorities. Whatever is done, it is key is that categories are well-defined, and enumerators (who are not sanitation specialists if a data collection firm is being used) understand the difference between different categories.

The JMP is still revising its “core questions” for household sanitation, but the latest JMP-endorsed questions are the module in the latest round of MICS here. The ones applicable to sharing are pasted below. So next time you’re doing an urban survey, best to use the below questions, unless you have a good reason not to! That way we’re all working towards consistent and comparable data on shared sanitation in the future.

MICS_san

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santype5city

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Preferences and constraints – when does container-based sanitation address the binding constraint to uptake?

By: IanRoss

In welfare economics, “preferences” denote which alternative goods or services someone would choose, based on the relative “utility” provided by each (more on utility another time). For example, when presented with a box of chocolates, my first choice is always a praline (P). But if only marzipan fruits (M) and brazil nut caramels (B) were left, I would choose the latter. This allows my preferences over a “set” of chocolates to be written as:

P B M

However, if I liked B and M equally, I would be “indifferent” towards them, written as:

B ~ M

Enough about chocolate. Let’s assume that I interviewed 1,000 people in an urban setting. I asked them about their preferences over various household sanitation options if there were no constraints like space or money, and I found that:

  1. People’s first choice would be a private household toilet if it were possible
  2. Preferences for other types of sanitation followed the order of categories of sanitation I set out in this post, giving the result:

Household private Household shared Communal Public Open defecation

This is called stated preference (what they told us) as opposed to revealed preference (what we observe in people’s actual choices).

Household shared was preferred to communal because of not having to leave the plot. Communal was preferred to public on the assumption it would be closer, cleaner and cheaper on average. The other preference relationships are obvious, though may not hold in all urban settings, e.g. there is a revealed preference for open defecation in some parts of India.

The interesting question is, if people aren’t able to fulfil a stated preference for a private household toilet, which constraints prevent them from doing so? Furthermore, which of those is binding? Interventions addressing other constraints will not increase demand unless they address the binding constraint.

I’ve been thinking about this every time container-based sanitation (CBS) is considered as an option in a city I’m working on. CBS comprises systems in which toilets collect excreta in sealable, removable containers for transport to treatment. Below is one example of a CBS service chain from SOIL in Haiti.

SOIL_cycle

Where would CBS fit into the above preference set? The answer would depend on which constraint the household was facing towards fulfilling their preference.

So, what are common constraints to uptake of private toilets in urban areas? Three factors I’ve seen most reported are:

  1. limited space – nowhere to build a toilet on the plot
  2. limited ability to pay (ATP) – not enough access to cash or finance to purchase
  3. limited willingness to pay (WTP) – investment not perceived as worth its opportunity cost

Land tenure and tenancy status are key, and closely related to WTP. People who own their home but are squatting on land may have ATP but not WTP, because they fear making sunk investments which would be lost in the event of eviction. Landlords may not have WTP for private toilets for tenants, since they will not benefit personally (though in theory they could increase rents – evidence on this is mixed). Tenants may be reluctant or unable to invest in a landlord’s property. The ATP constraint relates not only to inability to fund the absolute CapEx cost, but also to inability to spread it over time. There are more factors besides.

To my mind, CBS seems most appropriate where space and/or ATP are the binding constraints.

  • Space: CBS overcomes this by placing the toilet in an existing room rather than a new structure
  • ATP: CBS overcomes this, partially, by making sanitation a service with a small regular fee (like water), rather than an upfront capital investment.

CBS may also have its place in some settings where WTP is the binding constraint, but then its value proposition would have to be better than the alternative. From a tenancy/tenure perspective, a CBS investment is not a sunk cost.

Where does this leave CBS in the hypothetical preference set, then? Of course it would depend on the household e.g. what their alternatives are, whether they have a suitable room, their relative preference for leaving the household building / plot to use a toilet (which could be gendered). On average, I think it might look like this:

private CBS  shared communal  public open defecation

The symbol ≽ denotes  “weak” preference (“better than or equal in value to”), as opposed to “strict” preference ( “better than”). A CBS toilet is essentially a private toilet which is not in a room constructed for the purpose. So it offers many of the advantages of private toilets over shared ones (privacy, security, convenience etc.). I suggest weak preference above (≽) because whether CBS is preferred to an on-plot shared arrangement will very much depend on the setting. The same is true for the other relationships but probably less so. Whether a private toilet is preferred to CBS will depend on other factors too – a household with space and ATP would probably prefer a specific structure not taking up an existing room (allowing those in adjacent rooms to hear and smell…).

CBS is not a silver bullet for all urban sanitation challenges. However, it does have potential in some settings, especially informal settlements where space, ATP (cost-spreading) or tenancy/tenure are the binding constraint to uptake of improved sanitation.

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SOIL_cycle

✇WASHeconomics Blog

Recall bias and cost data

By: IanRoss

I’ve been working on costing a few programmes recently where the intervention happened between 3-10 years ago. Both used household surveys asking people what they spent (in cash and in kind) towards the original infrastructure output (CapEx), towards regular operational and maintenance (OpEx) and irregular capital maintenance (CapManEx). It’s got me thinking about the various recall bias issues involved.

Look at the graph below, which is completely hypothetical. Let’s assume it’s for a sanitation intervention amongst 1,000 households which happened in 2008. The y-axis is some measure of ‘data quality’ when you ask 1,000 households about expenditure. If you asked in 2008 how much they spent (cash and kind) to construct a toilet (CapEx – blue line), they’ll probably still have a good idea because it was very recent. However, as time goes by, they’ll forget exactly what they spent, so the blue line drops. Data quality will drop fast at first, but then plateau after a while because people are likely to remember the order of magnitude of  what they paid.

recall bias

For OpEx (orange line), which is by definition recurrent expenditure which occurs with a regularity of one year or less, it’s a different problem. If you ask people in 2009 about their OpEx, they won’t have that good an idea because they only have 1 year’s experience of using the toilet. Maybe they’ve cleaned it regularly but not spent much more money so far. Over time, they build up more experience of how much they tend to spend on OpEx and data quality becomes good.

CapManEx (grey line) is the hardest. It is recurrent expenditure occurring less than once a year (e.g. pit or tank emptying costs). So any time you ask people about it they’re less likely to have experienced it recently than with OpEx. Stuff normally works well when it’s new, so people are unlikely to experience CapManEx for a fair few years. With a toilet, for example, you’re only likely to need to empty the pit or septic tank 3-8 years after installation depending on numerous factors. So you only start getting likelihood of good data on CapManEx many years after the intervention, but even then it’s never going to be brilliant because many people may not have incurred it recently, and you have the same recall bias issues.

So when should you do your cost data collection? It depends on your objectives. If you’re most interested in CapEx, then do it ASAP. But if the lifecycle element is more important to your study, then it’s probably best to wait at least 3 years, maybe even 6-8 years if it’s the CapManEx you’re most interested in. You can always impute the CapEx from other sources or ask a different sample of people who constructed more recently. Of course the best case would be to get regular data with the same panel of households at intervals, but who is going to fund that…

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recall bias

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SUSTAINABLE WASH FINANCE SERIES: Blended Finance for Water Infrastructure: Hope or Hype?

This story is part of our series on sustainable WASH finance. Alex Money shares why more catalytic innovation is needed to have a transformative impact. This story was originally published on IRC’s blog. To view the original story, click here. By Alex Money  What is blended finance? Blended finance is a somewhat amorphous concept. A simple definition…

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SUSTAINABLE WASH FINANCE SERIES: Money From Waste? Revamp Your View on Sanitation

This story is part of our series on sustainable WASH finance. Over the next few weeks we will share innovative approaches to closing the financing gap for SDG6. This story was originally published on the World Bank’s Water Blog. To view the original article, click here. By Daniel Ddiba As an undergraduate student in Kampala, my…

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SUSTAINABLE WASH FINANCE SERIES: Finance and Marketing for CLTS and Rural WASH: Challenges and Opportunities in West and Central Africa

This story is part of our series on sustainable WASH finance. The CLTS Knowledge Hub held a four-day regional workshop in Saly, Senegal; the major aim was encouraging and engaging sanitation practitioners across fifteen West and Central African (WCA) countries for them to share knowledge and experiences, as well as challenges and innovations in regards to…

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SUSTAINABLE WASH FINANCE SERIES: Customers, Not Beneficiaries: Shifting Our perception of the Urban Poor and their Ability to Participate Financially in Water and Sanitation Service Delivery

By Kirk Anderson With nearly 1 billion people worldwide lacking access to clean water and more than 2 billion lacking access to a toilet, achieving Sustainable Development Goal 6 (Access to clean water and sanitation for all people) is a monumental task. The world needs strategies and mechanisms that move us forward quickly and sustainably.…

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SUSTAINABLE WASH FINANCE SERIES: Financing the Sector in Challenging Countries

This story is part of our series on sustainable WASH finance. Fixing the leaks to attract commercial investment for sustainable urban water services in sub-Saharan Africa and beyond. This story was originally published on IRC’s blog. To view the original story, click here. By Rolfe Eberhard  I was struck by the clear consensus that emerged from the…

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The difference between economic and financial analysis for WASH services

By: IanRoss

The distinction between economic analysis and financial analysis is not always straightforward. In this post I try to clarify this.

Definitions

I have previously defined WASH economics as “the study of how people make decisions about the allocation of scarce resources in the delivery and use of WASH services.” See that post for more discussion of definitions.

In turn, my working definition of WASH finance is “the study of how WASH services are paid for, including who pays, how and when”. More on this definition another time. Within the realm of “finance” it is important to distinguish between funding and financing, as is now becoming the norm. In a recent book chapter on equality in WASH funding and financing I co-authored with Richard Franceys, we explain this as follows:

“Funding is broadly defined as providing money which is not expected to be repaid. In the WASH context, funding usually comes from three sources: tariffs (including self-supply expenditure or user charges such as connection fees), government tax revenue, and donor transfers. Together, these are known as the “3Ts” framework, popularised by the OECD. In contrast, financing, is defined as providing money as a loan or equity in the expectation that it will be returned in full and with interest, in the case of debt, or dividends from profits, in the case of equity. In other words, funding is the provision of non-repayable money and financing is the provision of money which is repayable to the financiers.”

Turning to economic and financial analysis, I would characterise that as technical work which uses the perspective and methods of those two disciplines to appraise plans, projects and investments. The reason I emphasised the phrase “paid for” in the above definition of WASH finance is that it brings out the difference between economic and financial costs.

Economics costs vs. financial costs

Economic costs are the opportunity cost of resources (i.e. the value of the highest-value alternative use). Financial costs, meanwhile, are resources that are “paid for” (a turn of phrase borrowed from the health sector).

Not all resources used in the delivery of WASH interventions and programmes are paid for. Consider unpaid household time in programme participation or toilet construction, and the use of an asset that is donated to the programme, such as a vacuum truck. An estimate of the value of each of these resources would be excluded from a financial analysis but included in an economic analysis. This is because economic analyses should assess opportunity costs (defined above).

Underlying this is issue of valuation, i.e. what are things worth? Theories of value have been debated in economics since the discipline began. Financial costs are normally straightforwardly valued at the price paid. The complicated part is how to spread them over time – the financial cost of a programme in a given year is rarely the same as programme expenditure in that year.

Valuation of economic costs, however, is more tricky. There can be many competing ways to value an opportunity cost. For example, the opportunity cost of a person’s unpaid time in undertaking unskilled labour might be taken as (i) the minimum wage rate in that country for unskilled labour, (ii) 50% of that (reflecting the fact that the time may not have been allocated to income‐generating activity), or (iii) some other assumption based on another wage rate local to the setting (if the minimum wage is not a good reflection of market wages). The opportunity cost of a donated vacuum truck might be its estimated resale value in the open market. So, the total economic cost of a programme or intervention is the value forgone of all resources used.

Financial analysis implies the perspective of a given payer, whereas economic analysis usually (but not always) implies a societal perspective. So, economic evaluations (such as those employing cost-benefit or cost-effectiveness analysis) usually take a societal perspective. Planning and budgeting exercises, meanwhile, usually take the perspective of the institution that will pay for the programme of service. For example, the budget for an NGO’s rural water programme would only include the financial costs that would pass through their books. It would not include financial costs borne other stakeholders partners (such as local governments or households) covered from other revenue sources.

Types of economic and financial analysis 

There are many types of economic and financial analysis. All require cost analysis. Going into them is beyond the scope of this post. In brief, economic analysis is primarily concerned with efficiency (whether technical, productive or allocative) so includes things like economic evaluation (cost-benefit, cost-effectiveness), damage cost assessment, etc. but also assessment of economy and input/output relationships. Altogether, most of these things are part of Value for Money analysis (see diagram on p.5 of this). Financial analysis, meanwhile, includes things like funding gap analysis, cashflow analysis, willingness to pay assessment etc. – note the focus on covering costs, rather than on assessing efficiency.

The table below uses a few examples to illustrate some important of the purposes, and how the purpose drives the analytical perspective and type of cost used. More on this another time.

blogpost_-_fin_v_econ

Conclusion

My short (and perhaps flippant) summary of the difference between economics and finance is that “economics is about valuing stuff” and “finance is about who pays, how and when”. When considering an investment, both economic and financial analysis are important. In addition to knowing whether a project will have net benefits (i.e. is worth doing), it is important to know that it will be financially sustainable (i.e. the life-cycle costs can be covered).

 

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blogpost_-_fin_v_econ

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SUSTAINABLE WASH FINANCE SERIES: Want to Build Human Capital? Invest in WASH

This story is part of our series on sustainable WASH finance. At the World Bank Group annual meeting of finance ministers, donors and civil society representatives in October one buzzword was present everywhere – ‘human capital’. Dan Jones, Advocacy Coordinator at WaterAid UK, argues that investing in water, sanitation and hygiene shouldn’t be overlooked. This story was…

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