1 Projection of health risks due to exposure to floodwater pathogens Psyche Fontanos and Kensuke Fukushi TODIAS/IR3S, the University of Tokyo
Status of sewerage and sanitation 2 < 2% of population served by sewerage system in Indonesia (Asian Development Bank, 2004)
Risk Assessment 3 Determine the risks of infection from exposure to pathogens in the flood water. Exposure to pathogens through daily activities
Quantitative microbial risk assessment (QMRA) 4 http://qmrawiki.msu.ed u
Hazard Identification 5 Pathogens in urban floods (Phanuwan et al., 2006; Pardue et al., 2005) Several pathogens cause waterborne illnesses, however due to limitation of data for this study only Escherichia coli is considered It has been shown that the presence of E. coli also indicates the presence of other pathogens The indicator in freshwater that correlates best with health outcomes is E. coli (Pruss, 1998)
Dose-response model 6 Beta Poisson model for E. coli （ Haas et al ., 1999 ） For single infection risk: − α ( ) d = − + − α 𝑒 = 𝐷 𝑦 𝐽 𝑦 𝑈 1 / P ( d ) 1 1 2 1 N 50 where d, dose C, pathogen concentration α, slope parameter = 0.1778 (derived ) I, ingestion rate N50, medium infectious dose = 8.6 × 10 7 (derived) T, duration of exposure For annual infection risk: [ ] = − − n P 1 1 P ( d ) annual where n, number of exposure times per year
Exposure Assessment 7 Direct ingestion of contaminated water through swimming and swim-like activities Flood water Flood water Concentration of pathogen (E. coli) in the water environment Indirect ingestion of contaminated water through hand to mouth transfer Exposure pathway Exposure pathway
Exposure Assessment Assumptions (example for Jakarta) 8 Non-adults Adults Inundatio n depth Exposure Exposure Exposure Exposure (cm) Pathway Duration Pathway Duration < 20% of time < 25% of time 10 – 50 Indirect outdoor spent Indirect outdoor spent ingestion ingestion in contact with in contact with water water < 40% of time < 50% of time 50 - 100 Direct outdoor spent Indirect outdoor spent ingestion ingestion in contact with in contact with water water < 60% of time < 75% of time 100 - 200 Direct outdoor spent Direct outdoor spent ingestion ingestion in contact with in contact with water water < 80% of time < 100% of time Direct outdoor spent Direct outdoor spent > 200 ingestion ingestion in contact with in contact with water water
Exposure Assessment Assumptions 9 Symbol, Symbol, Parameter Parameter Remarks Remarks Sources Sources unit unit C E 8 - 65 x 10 3 CFU/ml Concentration of E. Kido et al (2009); coli Palupi et al (1995); Phanuwan (2006) US EPA (2000) Water Ingestion Rate I w , Non-adults: 10-50 ml/h ml/hr Adults :10 ml/h (Indirect ingestion by hand to mouth transfer) I s ,ml/hr Non-adults: 0-205 ml/hr Dufour et al (2006) Water Ingestion Rate (Direct ingestion) Adults : 0-71 ml/hr US EPA (1997) Time spent outdoors T, 5th - 20; 25th - 60; 50th - 150; hr/day 75th - 320; 90th - 511; 95th - 615) F Fraction of outdoor Non-adults (10-50 cm: up to 20%; Assumed, varies time spent in water 50-100cm: up to 40%; 100-200cm: according to up to 60%; over 200cm: up to inundation levels 80%) Adults (10-50 cm: up to 25%; 50- 100cm: up to 50%; 100-200cm: up to 75%; over 200cm: up to 100%) Dose-response model N 50 = 8.6x10 7 Haas (1999) α = 0.1778
Risk characterization 10 10 Probabilistic risk calculation Monte Carlo simulation Schematic showing the basic principle behind the Monte Carlo Simulation (http://www.vertex42.com/ExcelArticles/mc/MonteCarloSimulation.html)
Risks of infection Risk of infection Risk of infection (mean) (mean) Total Total Inundation depth Inundation depth Single Single- (cm) (cm) Adults Adults Non Non-adults adults Annual Annual risk 1 risk 10 – 50 0.0019 0.0001 0.0007 0.0086 50 - 100 0.0032 0.0016 0.0021 0.0252 100 - 200 0.0046 0.0023 0.0030 0.0363 > 200 0.0053 0.0877 0.0630 0.542 1 30% of total population is children (AIPA report) 11 11
Generation of Maps 12 12 ArcGIS 10.1 by the US Environment Research Institute (US ESRI) was used for generating maps Map of daily risk Map of daily risk Data provided by JICA and Yachiyo Engineering Inundation map Inundation map to create inundation and risk maps Land use map
Scenarios (example for Jakarta) 13 13 Clima mate te Urban aniza izatio tion n Incre rease ased d Sea l ea level evel High igh t tide ide Land and chan hange ge (%) %) rate ate of f rise ise ( (cm) cm) leve evel subsi siden dence ce scena nario rio rain ainfa fall ( l (%) %) (m) m) P 62.3 (2008) 0 39 1.15 0 – 5.9 B1 77.7 (2050) 8 39 1.15 0 – 5.9 A1F1 77.7 (2050) 17 39 1.15 0 – 5.9 Scena nario rio Conte tents nts SQ Status quo scenario The existing flood control infrastructure would be maintained by 2050. MP Master plan scenario The flood control infrastructure in 2050 would be based on the implementation of the existing Master Plan (without the Ciliwung Floodway) MP + PS Master Plan + The existing Master Plan would be strengthened with Strengthening of Pumping Pumping station by 2050. station
Inundation maps (example for Jakarta) 14 14 2050_F_MP_A1F1_v0_100 2050_F_MP_A1F1_v2_100 A B C Due to impacts of climate change, inundation area is increased about 8-14% (A&B) Due to land subsidence, inundation area is increased about 15-20% (B&C) Source: GIS shapefiles from Yachiyo Engineering Ltd.
Risk map (example for Jakarta) 15 15 Risks of infection from E. coli due to the incidental ingestion of flood water were determined to be 0.0086, 0.0252, 0.0363, and 0.542 corresponding to inundation levels from 10-50 cm, 50-100 cm, 100- 200 cm, and above 200 cm, respectively. The risk of infection doesn’t necessarily translate to development of disease due to the differing conditions and immunities of individuals which are affected by age, lifestyle, among others.
Next step 16 16 Model improvement Secondary infection in house and offices Asymptomatic infection for viruses Human-to-human infection in community/across community Calibration of model Hospital Pharmacy Model expansion Urban planning (land use and drainage)
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