the impact of water and sanitation on diarrhoeal disease burden and over-consumption of antibiotics

73 Pages·2016·3.05 MB·English

THE IMPACT OF WATER AND
SANITATION ON DIARRHOEAL DISEASE BURDEN
AND OVER-CONSUMPTION OF ANTIBIOTICS
PRESENTED TO THE REVIEW ON ANTIMICROBIAL RESISTANCE
Pablo Araya, Julia Hug, Genevieve Joy, Felicia Oschmann, Susana Rubinstein
Master of Public Administration
London School of Economics and Political Science
March 2016
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N PRESENTED TO THE REVIEW ON ANTIMICROBIAL RESISTANCE
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N O Pablo Araya, Julia Hug, Genevieve Joy, Felicia Oschmann, Susana Rubinstein
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IC London School of Economics and Political Science
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March 2016
A C K N O W L E D G E M E N T S
This is a final capstone report for the Master of Public Administration (MPA) at the London School of
Economics and Political Science (LSE). This report was conducted under the supervision of the AMR
Review based at The Wellcome Trust in London, UK. Our heartfelt thanks go the entire Review for their
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support and close cooperation throughout the whole process, particularly Hala Audi, Jeremy Knox,
Anthony McDonnell and Anjana Seshradi. We also wish to humbly thank Lord Jim O’Neill, Chairman of
the Review, for his encouragement and insights. TH
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We began the project in October 2015 with little prior exposure to the topic. Our understanding and PA
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analysis benefited from the guidance of many experts who took the time to meet with us and distil T O
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years of research into short meetings. W
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The section on costs was shaped by the inputs of Guy Hutton, Senior Economist, World Bank Water A
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and Sanitation Program (WSP), who dedicated time and shared information that greatly informed our D
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findings. A
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The section on disease burden and the effects of different interventions was influenced by the work IO
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and advice of Val Curtis, Katie Greenland, and Sandy Cairncross of the London School of Hygiene and O
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Tropical Medicine. Neil Woodford, the Head of the Antimicrobial Resistance and Healthcare Associated D
Infections (AMRHAI) Reference Unit at Public Health England, provided us with an understanding of IAR
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the science of AMR and its potential impact in a globalised world. Mike Sharland, consultant in paedi- HO
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atric infectious disease at St George’s University Hospitals NHS Foundation Trust, was extremely gener- A
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ous with his time and opened our minds to even more research options within this field. DIS
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Eduardo Pisani and Nina Grundmann at the International Federation of Pharmaceutical Manufacturers E B
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and Associations (IFPMA) provided us with valuable insights into the pharmaceutical industry’s R
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perspective on AMR, and emphasised the need for an integrated response across private and public EN
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sectors. At LSE, we received invaluable guidance on our models from Estela Barbosa, Jeroen Luyten N
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and Huseyin Naci. O
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Our project benefited from the oversight of two supervisors. Professor Patrick Dunleavy set us on the O
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right course by extolling the virtues of storyboarding and correcting our course when we lost our way. SU
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Brett Meyer provided useful feedback and advice in the second half of the project. P
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We also wish to thank Camilo Niño for his beautiful design work and Lola Conte and Sophia Deckel for OF
their exceptional support. AN
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And finally, we wish to thank the MPA office, especially Jess Frankland, Babken Babajanian and Michelle T
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Batten, for putting up with many emails and even more room bookings. S
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TABLE OF
CONTENTS
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ACKNOWLEDGEMENTS 3 T
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ABBREVIATIONS AND ACRONYMS 7 P
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LIST OF TABLES, FIGURES AND BOXES 9 F W
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EXECUTIVE SUMMARY 11 A
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1. INTRODUCTION 13 AN
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1.1. Objectives 13 ION
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1.2. Scope and approach 13 N
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1.3. Structure and methodology 14 IA
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2. BACKGROUND 14 E
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2.1. Antimicrobial resistance 14 EA
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2.2. WASH: burden and definitions 15 E B
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3. THE COSTS OF PROVIDING SAFE ACCESS TO WATER AND SANITATION 17 EN
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3.1. Cost estimates of WASH interventions 19 OV
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3.2. WASH overview and costs by country 20 R-
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3.3. Achieving WASH: mitigating and promoting factors beyond costs 21 ON
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4. ACCESS TO SAFE WASH INFRASTRUCTURE HAS THE POTENTIAL TO HIGHLY REDUCE 23 TIO
DIARRHOEAL DISEASE IN THESE COUNTRIES N
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4.1. The link between diarrhoea and WASH 23 NT
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4.2. Data 24 IO
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4.3. Disease burden probability model 26 IC
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4.4. Results 27
4.5. “Bang for your buck” analysis 28
4.6. Analysis 30
4.7. Discussion and policy implications
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5. REDUCTION OF DIARRHOEAL DISEASE CAN HAVE A LARGE IMPACT ON THE OVERUSE OF ANTIBIOTICS 31
5.1. Diarrhoea, antibiotics and AMR: the missing link 31
5.2. Antibiotic usage for diarrhoea 32
5.3. Diarrhoea and antibiotics: quantifying the relationship 35
6. FINAL THOUGHTS AND RECOMMENDATIONS 40
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7. CONCLUSION 42
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HE IM BIBLIOGRAPHY 43
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CT ANNEXES
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AT Annex 1. Terms of reference 55
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R A Annex 2. Methodology 57
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A Annex 2B. Sensitivity analysis 60
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ITA Annex 2C. Reference of literature on effect of WASH interventions 63
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ON Annex 4. Overview of the cost literature 69
DIA Annex 5. Cost of India’s national sanitation goals 70
RR Annex 6. Main country statistics 72
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ABBREVIATIONS
AND ACRONYMS
AMR Antimicrobial resistance
AMRHAI Antimicrobial Resistance and Healthcare Associated Infections
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CDDEP Center for Disease Dynamics, Economics & Policy
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CEBDS Conselho Empresarial Brasileiro para o Desenvolvimento Sustentável H
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(The Brazilian Business Council for Sustainable Development) IM
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CLTS Community-led total sanitation T
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CBA Cost-benefit analysis A
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CDC Centers for Disease Control and Prevention AN
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CEA Cost-effectiveness analysis N
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CI Confidence interval IO
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DALY Disability-adjusted life year D
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DHS Demographic and Health Surveys Program H
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ECDC European Centre for Disease Prevention and Control D
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FSM Faecal sludge management S
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GDP Gross domestic product D
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GWA Gender and water alliance N
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HI High income countries R
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IGBE Instituto Brasileiro de Geografia e Estatística (Brazilian Institute for Geography and Statistics) S
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IMF International Monetary Fund IO
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IO International organisation A
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IRC International Rescue Committee IO
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JMP Joint Monitoring Programme for Water Supply and Sanitation S
LAC Latin America and the Caribbean
LMIC Low- and middle-income countries
M&O Maintenance and operations
MDG Millennium Development Goal
NGO Non-governmental organisation
NEEDS National economic empowerment and development strategy
NGP Nirmal Gram Puraskar
OECD Organization for Economic Cooperation and Development
OHCHR Office of the United Nations High Commissioner for Human Rights
ORS Oral rehydration salts
PAF Population attributable factor
Plansab Plano Nacional de Saneamento Básico (National Sanitation Plan)
PPP Purchasing power parity
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R&D Research and development
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E IM RCT Randomised control trial
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CT RR Relative risk reduction
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W SDG Sustainable Development Goals
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A SNIS Sistema Nacional de Informações Sobre Saneamento (National Sanitation Information System)
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A SUS Sistema Único de Saúde (Unified Health System)
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N D UN United Nations
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RH UNICEF United Nations International Children’s Emergency Fund
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AS WASH Water, sanitation and hygiene
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LIST OF TABLES,
FIGURES AND BOXES
FIGURE 1.1: Project overview 12
FIGURE 2.1: How AMR breeds 15
FIGURE 2.2: History of AMR 15
FIGURE 2.3: Diseases contributing to the disease burden 16
FIGURE 2.4: Sustainable Development Goals (SDGs) related to water and sanitation, 2015-2030 16
FIGURE 2.5: Number of people practising open defecation (millions), 2014 16 9
FIGURE 3.1: Definition ladders for sanitation, drinking water and handwashing 17
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FIGURE 3.2: Baseline access to sanitation, 2015 18 HE
FIGURE 3.3: Baseline access to water, 2015 18 IMP
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TABLE 3.1: Percentage of country sources for WSP estimates 19 T O
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TABLE 3.2: Annual costs of universal, safe access to WASH by 2030 20 WA
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FIGURE 4.1: F-Diagram: routes of faecal disease transmission and protective barriers 23 R A
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FIGURE 4.2: Relative RR for diarrhoeal disease from water interventions 25 D S
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FIGURE 4.3: Relative RR for diarrhoeal disease from sanitation interventions 25 IT
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FIGURE 4.4: Disease burden model for the effect of WASH interventions until 2030 26 IO
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TABLE 4.1: Gains in diarrhoeal burden from water intervention 27 N
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TABLE 4.2: Gains in diarrhoeal burden from sanitation intervention 27 IAR
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TABLE 4.3: “Biggest bang for the buck” analysis per person per year to reach safe WASH by 2030 29 OE
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TABLE 4.4: “Biggest bang for the buck” analysis per person per year to reach safe WASH by 2030 in rural areas 29 DIS
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TABLE 4.5: “Biggest bang for the buck” analysis per person per year to reach safe WASH by 2030 in urban areas 29 AS
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TABLE 4.6: CEA using cost per DALY averted to reach safe WASH by 2030 29 BU
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FIGURE 5.1: Frequency of non-prescription use of antimicrobials in the general population 32 EN
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FIGURE 5.2: Percentage of children born in the at least 3 years preceding the survey with diarrhoea 33 D O
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TABLE 5.1: Percentage of children born in the at least 3 years preceding the survey with diarrhoea who received antibiotics 33 ER
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TABLE 5.2: Results of local studies 34 ON
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TABLE 5.3: Range to estimate the cases of diarrhoea treated with antibiotics 35 MP
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TABLE 5.4: Average episode per person per year by age group 35 ION
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TABLE 5.5A Cases treated with antibiotics in 2015 for water 36 F A
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TABLE 5.5B: Cases treated with antibiotics in 2015 for sanitation 36 IB
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TABLE 5.6: Estimated cases treated with antibiotics in 2030 in the do-nothing scenario 36 TIC
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TABLE 5.7. Estimated cases treated with antibiotics in 2030 in the intervention scenarios 36
TABLE 5.8. Reduction in antibiotic consumption in 2030 from a do-nothing to an intervention scenario 37
FIGURE 5.3. Impact of WASH intervention on antibiotic consumption 37
BOX 5.1: Brazil and the case of the 2014 FIFA World Cup 38
FIGURE 6.1: Morbidity surveillance pyramid 50
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