[Malaysia] Understanding and managing the risk of water related diseases under hydrometeorological extremes
Lead Research Organisation:
Imperial College London
Department Name: Civil & Environmental Engineering
Abstract
Globally, water-related diseases are a major obstacle to sustainable development (WHO, 2018). Many of these diseases, such as Cholera and Hepatitis A, have been successfully phased out in Malaysia. However, leptospirosis and malaria still affect Malaysians every year. The annual incidence rate of Leptospirosis is actually increasing, from 0.97 cases per 100,000 population in 2004 to 12.47 per 100,000 in 2012.
It is well known that leptospirosis and malaria are strongly linked to environmental conditions, and humidity and temperature in particular. Although scientific understanding of this link is advancing at a rapid pace, it is still very difficult to build computational models that make quantitative forecasts of outbreaks. Yet such systems are indispensable for proactive disease management, and to optimise the allocation of resources for medical prevention and interventions.
A major difficulty with predicting outbreaks of water-related diseases is the large number of driving factors, which span the environmental and socio-economic realms. Additionally, many of the processes that link the driving factors with disease outbreaks, are highly non-linear and difficult to represent in computational algorithms.
This proposal therefore sets out to explore the use of artificial intelligence approaches to identify and model the physical and microbiological interactions that lead to conditions favouring disease occurrences, with the goal of developing an early warning system for disease outbreaks. The complexity and non-linearity in the processes makes AI methods such as the neural network approach highly promising as it is inherently suited to problems that are mathematically difficult to describe and highly non-linear.
The scientific field of artificial intelligence is developing at a very rapid pace. This evolution is driven by the exponentially increasing amount of information available online (often referred to as the "big data" era), much of which is highly unstructured and diverse (e.g., data from social media such as twitter feeds and news posts). This has resulted in the development of many novel and powerful algorithms and routines. However, its exploration in the context of water-related diseases is still very limited. Therefore, we propose to leverage these breakthroughs, by testing and adapting these new methodologies to advance predictive modelling of the link between hydrometeorological extremes and water-related diseases. The proposed research combines extensive compilation, synthesis and integration of socio-demographic and infrastructural data alongside data of environmental extremes, with novel computational algorithms to "learn" from the datasets and leverage the outcomes to improve operational forecasting systems.
We have assembled a world-leading consortium of scientists that combines expertise on hydrometeorological extremes, artificial intelligence and community health issues. We will use the Malaysian state of Negeri Sembilan as a case study, and will work in close collaboration with the State Department of Health. This will allow us to access historical records that include patients' demographic information. More recently, risk assessment have been conducted using questionnaires that includes assessment of water supply and drainage infrastructure. The epidemiological data will be complemented by environmental data from the Department of Meteorology and the Department of Irrigation and Drainage (which are either available for academic use for free or a small fee), and monthly water quality monitoring data from local District Offices.
References
WHO, 2018. http://www.who.int/water_sanitation_health/diseases-risks/diseases/diarrhoea
It is well known that leptospirosis and malaria are strongly linked to environmental conditions, and humidity and temperature in particular. Although scientific understanding of this link is advancing at a rapid pace, it is still very difficult to build computational models that make quantitative forecasts of outbreaks. Yet such systems are indispensable for proactive disease management, and to optimise the allocation of resources for medical prevention and interventions.
A major difficulty with predicting outbreaks of water-related diseases is the large number of driving factors, which span the environmental and socio-economic realms. Additionally, many of the processes that link the driving factors with disease outbreaks, are highly non-linear and difficult to represent in computational algorithms.
This proposal therefore sets out to explore the use of artificial intelligence approaches to identify and model the physical and microbiological interactions that lead to conditions favouring disease occurrences, with the goal of developing an early warning system for disease outbreaks. The complexity and non-linearity in the processes makes AI methods such as the neural network approach highly promising as it is inherently suited to problems that are mathematically difficult to describe and highly non-linear.
The scientific field of artificial intelligence is developing at a very rapid pace. This evolution is driven by the exponentially increasing amount of information available online (often referred to as the "big data" era), much of which is highly unstructured and diverse (e.g., data from social media such as twitter feeds and news posts). This has resulted in the development of many novel and powerful algorithms and routines. However, its exploration in the context of water-related diseases is still very limited. Therefore, we propose to leverage these breakthroughs, by testing and adapting these new methodologies to advance predictive modelling of the link between hydrometeorological extremes and water-related diseases. The proposed research combines extensive compilation, synthesis and integration of socio-demographic and infrastructural data alongside data of environmental extremes, with novel computational algorithms to "learn" from the datasets and leverage the outcomes to improve operational forecasting systems.
We have assembled a world-leading consortium of scientists that combines expertise on hydrometeorological extremes, artificial intelligence and community health issues. We will use the Malaysian state of Negeri Sembilan as a case study, and will work in close collaboration with the State Department of Health. This will allow us to access historical records that include patients' demographic information. More recently, risk assessment have been conducted using questionnaires that includes assessment of water supply and drainage infrastructure. The epidemiological data will be complemented by environmental data from the Department of Meteorology and the Department of Irrigation and Drainage (which are either available for academic use for free or a small fee), and monthly water quality monitoring data from local District Offices.
References
WHO, 2018. http://www.who.int/water_sanitation_health/diseases-risks/diseases/diarrhoea
Planned Impact
The proposed project arose from one of the major research priorities identified during a stakeholder engagement session as part of a workshop in Belum Forest in August 2017. The workshop was funded by a Newton Fund Researcher Links grant awarded to Dr Zulkafli and colleagues. As a result, the proposed research is strongly demand driven.
In order to maximise the impact of the proposed research, we will work closely with the crucial support from the State Department of Health, Negeri Sembilan. To ensure proper end-user buy-in and compatibility with operational procedures, a meeting was held on 8 February 2018 with the Head of Communicable Disease Control Unit. The current proposal is written in consultation with medical doctors in charge of surveillance and response to outbreaks.
Our pathways to impact strategy is based on 4 pillars:
" A strong engagement with our project partners
The Malaysian team will hold frequent follow-up meetings throughout the project with the State Department of Health, and the Communicable Disease Control Unit as well as Vector-borne Disease Control Unit in particular. Through this partner, we will further extend our network of potential end-users, for instance by reaching out to other states within Malaysia, and potentially in the rest of South East Asia.
" Usability and availability of project outcomes
The proposed research is very applied and will create outputs that are usable in an operational setting, in particular the forecasting model. Throughout the development of this model, we will work closely with potential end-users of these outputs to ensure the compatibility with existing systems and maximise the usability. For instance, we refrain from using commercial software solutions, but instead rely upon open-source modelling frameworks, such as the very extensive set of AI toolboxes available in the R statistical modelling environment.
" Engagement of the private sector
The investigator team has a track record of working with the private sector. We aim to engage private companies, and SMEs in particular, from the start of the project to maximise technology transfer. We identify two specific technologies that may be relevant: (1) disease forecasting services; and (2) low-cost sensing. For the former, we aim to work with SMEs in the sector of weather services. For the low-cost sensors we aim to connect to the thriving innovation community in Malaysia. For instance, Buytaert's group already sources components of the sensor platform from small company based in Kuala Lumpur (Rocketscream.com). Specific activities may include training sessions, and active participation in virtual innovation networks such as the Arduino and Internet of Things online forums.
" Engagement with the international disaster risk reduction community
The UK team in particular, has excellent contacts with the international disaster risk reduction community, for instance through their engagement with the UNESCO Sendai Framework for Disaster Risk Reduction (UNISDR) as part of their involvement in the NERC programme on "Science for Humanitarian Emergencies and Resilience" (SHEAR). Relevant activities include attendance to UNESCO Knowledge Fora (most recently in October 2017), production of policy briefs, organisation of conference sessions in policy-oriented events such as the World Water Forum.
Further details on these activities and their context is provided in the "Pathways to Impact" attachment.
In order to maximise the impact of the proposed research, we will work closely with the crucial support from the State Department of Health, Negeri Sembilan. To ensure proper end-user buy-in and compatibility with operational procedures, a meeting was held on 8 February 2018 with the Head of Communicable Disease Control Unit. The current proposal is written in consultation with medical doctors in charge of surveillance and response to outbreaks.
Our pathways to impact strategy is based on 4 pillars:
" A strong engagement with our project partners
The Malaysian team will hold frequent follow-up meetings throughout the project with the State Department of Health, and the Communicable Disease Control Unit as well as Vector-borne Disease Control Unit in particular. Through this partner, we will further extend our network of potential end-users, for instance by reaching out to other states within Malaysia, and potentially in the rest of South East Asia.
" Usability and availability of project outcomes
The proposed research is very applied and will create outputs that are usable in an operational setting, in particular the forecasting model. Throughout the development of this model, we will work closely with potential end-users of these outputs to ensure the compatibility with existing systems and maximise the usability. For instance, we refrain from using commercial software solutions, but instead rely upon open-source modelling frameworks, such as the very extensive set of AI toolboxes available in the R statistical modelling environment.
" Engagement of the private sector
The investigator team has a track record of working with the private sector. We aim to engage private companies, and SMEs in particular, from the start of the project to maximise technology transfer. We identify two specific technologies that may be relevant: (1) disease forecasting services; and (2) low-cost sensing. For the former, we aim to work with SMEs in the sector of weather services. For the low-cost sensors we aim to connect to the thriving innovation community in Malaysia. For instance, Buytaert's group already sources components of the sensor platform from small company based in Kuala Lumpur (Rocketscream.com). Specific activities may include training sessions, and active participation in virtual innovation networks such as the Arduino and Internet of Things online forums.
" Engagement with the international disaster risk reduction community
The UK team in particular, has excellent contacts with the international disaster risk reduction community, for instance through their engagement with the UNESCO Sendai Framework for Disaster Risk Reduction (UNISDR) as part of their involvement in the NERC programme on "Science for Humanitarian Emergencies and Resilience" (SHEAR). Relevant activities include attendance to UNESCO Knowledge Fora (most recently in October 2017), production of policy briefs, organisation of conference sessions in policy-oriented events such as the World Water Forum.
Further details on these activities and their context is provided in the "Pathways to Impact" attachment.
Publications
Zhang L
(2023)
Highly Ethylene-Selective Electroreduction CO2 Over Cu Phosphate Nanostructures with Tunable Morphology
in Topics in Catalysis
Jayaramu V
(2023)
Leptospirosis modelling using hydrometeorological indices and random forest machine learning.
in International journal of biometeorology
Rahmat F
(2020)
Exploratory Data Analysis and Artificial Neural Network for Prediction of Leptospirosis Occurrence in Seremban, Malaysia Based on Meteorological Data
in Frontiers in Earth Science
Rahmat F
(2019)
Prediction model of Leptospirosis Occurrence for Seremban (Malaysia) using Meteorological Data
in International Journal of Integrated Engineering
Description | · Hydrometeorological patterns appear to drive leptospirosis risk in some but not all settings · Where hydrology appears to play an important role, flow and storage (soil moisture) related variables appear to be better predictors than rainfall in many of the historical case studies considered. Hydrological monitoring may, in those settings, have value for infection risk prediction. · Hygiene and solid waste management related factors may have a dominant effect on leptospirosis risk in places that are not flood prone, such as the original case study locus of Negeri Sembilan, due to their favourable effect on rat populations and their concentration. · Extreme hydrometeorological indicators perform better at predicting incidence of leptospirosis than average indicators, in some cases. |
Exploitation Route | Developing further the Artificial Intelligence models and approaches that the project developed to predict disease outbreaks. The project has begun to generate water level data that can be integrated in future hydro-epidemiological research on leptospirosis. |
Sectors | Environment Healthcare |
Description | Throughout the project there has been sustained engagement with an increasing number of Malaysian state health departments (first Negeri Sembilan, then Pahang and Kelantan) who are interested in the predictive model developed by Fariq Rahmat. This has created lasting ties between the health departments and the researchers at UPM. The water level monitoring infrastructure built will continue to generate useful hydrological data. In addition, because of this work, the project has gained visibility in Malaysia, also reaching a national audience of the general public through a tv news broadcast in February 2023 |
First Year Of Impact | 2021 |
Sector | Healthcare |
Impact Types | Policy & public services |
Description | Telemetry hydrological data analysis using R, 2022, Department of Irrigation and Drainage Ampang |
Geographic Reach | Local/Municipal/Regional |
Policy Influence Type | Participation in a guidance/advisory committee |
Title | Hydro-epidemiological data for Leptospirosis for areas in Brazil, Malaysia, Philippines, Argentina, China and Sri Lanka, 1978-2020 |
Description | This dataset contains Leptospirosis case numbers for a number of place studies in Brazil, Malaysia, Philippines, Argentina, China and Sri Lanka. Leptospirosis case numbers are provided as weekly or monthly case numbers and cover the period 1978 to 2020, although timelines vary within place studies. Area-weighted daily average hydrometeorological variables are also included: precipitation, river discharge and soil moisture. The data have been collected and collated for a global analysis of the effect of hydrometeorological extremes on leptospirosis infection risk. Also included are the spatial polygons for each of the place studies. |
Type Of Material | Database/Collection of data |
Year Produced | 2023 |
Provided To Others? | Yes |
URL | https://catalogue.ceh.ac.uk/id/56f42170-3678-4586-b8c8-9b05f03125e1 |
Description | Ongoing collaboration with project partner university UPM (Universiti Putra Malaysia) |
Organisation | Putra Malaysia University |
Country | Malaysia |
Sector | Academic/University |
PI Contribution | - we perform hydrological monitoring (using low-cost sensors developed in our group at Imperial College) and modelling - we play a mentoring role for the Malaysian PhD students and Master's students - we will lead on publications from the project that involve hydrological modelling - we are organising the annual project meeting in the summer of 2020 - we organised 5 online project meetings (2020-2021) and an in-person/online hybrid meeting (2022) - Simon De Stercke is an official supervisor of two PhD students and a Master's student at UPM |
Collaborator Contribution | - UPM have two PhD students (of whom one discontinued their PhD in 2020) and a Master's student working on this project, who are performing spatial and temporal modelling, predictive modelling, and secondary and primary (survey) data collection. - UPM have organised the annual project meeting in the summer of 2019. |
Impact | The collaboration is fruitful with a published paper, many conference presentations, and many papers in the pipeline. The collaboration is multi-disciplinary, involving human behaviour, hydrology, machine learning, spatial analytics, and epidemiology. |
Start Year | 2019 |
Title | Random forest model for leptospirosis prediction using hydrometeorological indices [Software]. |
Description | For more information, please kindly refer to Leptospirosis modelling using hydrometeorological indices and random forest machine learning |
Type Of Technology | Software |
Year Produced | 2023 |
Open Source License? | Yes |
Impact | Application of the model was published as Jayaramu, Veianthan, Zed Zulkafli, Simon De Stercke, Wouter Buytaert, Fariq Rahmat, Ribhan Zafira Abdul Rahman, Asnor Juraiza Ishak, Wardah Tahir, Jamalludin Ab Rahman, and Nik Mohd Hafiz Mohd Fuzi. 'Leptospirosis Modelling Using Hydrometeorological Indices and Random Forest Machine Learning'. International Journal of Biometeorology, 31 January 2023. https://doi.org/10.1007/s00484-022-02422-y. |
URL | https://zenodo.org/record/7683409 |
Description | Machine learning training to JKNSS staff |
Form Of Engagement Activity | Participation in an activity, workshop or similar |
Part Of Official Scheme? | No |
Geographic Reach | Regional |
Primary Audience | Professional Practitioners |
Results and Impact | The UPM researchers conducted a half-day machine learning training to staff at JKNSS, the health department of Negeri Sembilan state, who are project stakeholders. Negeri Sembilan state is our case study. |
Year(s) Of Engagement Activity | 2019 |
Description | Malaysian national news item ""Leptospirosis cases can be detected as early as two to 18 weeks in a location" about the UnderWRiDE project |
Form Of Engagement Activity | A press release, press conference or response to a media enquiry/interview |
Part Of Official Scheme? | No |
Geographic Reach | National |
Primary Audience | Public/other audiences |
Results and Impact | 3+ min Malaysian national news item about the project, including the predictive model, its capabilities, and the low-cost sensors for water level monitoring. We suspect that at the very least spectators learned more about leptospirosis and the risk of infection through this broadcast. The title of the news item is "Kes kencing tikus mampu dikesan seawal dua hingga 18 minggu di sesuatu lokasi" or "Leptospirosis cases can be detected as early as two to 18 weeks in a location" |
Year(s) Of Engagement Activity | 2023 |
URL | https://www.youtube.com/watch?v=s_HQEgv6wlc |
Description | Meeting to introduce water level sensors to JKNNS (health department stakeholder) |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | Local |
Primary Audience | Professional Practitioners |
Results and Impact | In this meeting, the UPM collaborators presented to the JKNNS the operation of the sensors used for participatory monitoring. They also discussed what factors must be considered in deciding the location for sensor installation such as what makes an area physically suitable, and permission that may be required from certain authorities. |
Year(s) Of Engagement Activity | 2021 |
Description | Meeting with health department (JKNNS) of Negeri Sembilan |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | Local |
Primary Audience | Professional Practitioners |
Results and Impact | Our UPM collaborators updated the JKNSS on our progress and the current output on spatial and temporal prediction of leptospirosis, including our publication plans. There was also a discussion on the planning of sensor installation for participatory monitoring activities, starting from several suitable areas to install the sensors that were suggested by the UPM collaborators |
Year(s) Of Engagement Activity | 2021 |
Description | Oral presentation at Water Security and Climate Change Conference 2021: "Leptospirosis risk from hydrometeorological patterns under climate change" |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Other audiences |
Results and Impact | Presentation in a well-attended session at the Water Security and Climate Change conference, titled "Building Resilience to Hydrometeorological Hazards in Southeast Asia", which brought together several NERC-funded programmes working on hydrometeorological hazards in South-East Asia. The presentation generated questions from the audience. |
Year(s) Of Engagement Activity | 2021 |
URL | https://watersecurity.info/timetable/event/building-resilience-to-hydrometeorological-hazards-in-se-... |
Description | Oral presentation at the AGU Fall Meeting 2020: GH022-05 - Integration of Spatiotemporal Data in The Development of AI-fEaL: Artificial Intelligence for Early Warning of Leptospirosis in Negeri Sembilan, Malaysia |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Other audiences |
Results and Impact | Presentation about the predictive model for leptospirosis incidence that was developed under the UnderWRiDE project, in an hour-long session with other researchers titled "GH022 Early Warning Systems for Infectious Disease Based on Climate and Environmental Variability". Presentations were followed by a discussion and question-and-answer. |
Year(s) Of Engagement Activity | 2020 |
URL | https://agu.confex.com/agu/fm20/meetingapp.cgi/Paper/690749 |
Description | Participated in meeting between UNDP Accelerator Labs and Imperial College London on SDG6 |
Form Of Engagement Activity | Participation in an activity, workshop or similar |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Third sector organisations |
Results and Impact | A meeting organized by the Global Development Hub at Imperial College London, to create a network between development research at Imperial College London and UNDP offices in developing countries. |
Year(s) Of Engagement Activity | 2021 |
Description | Poster and oral presentation at the AGU Fall Meeting 2020: "GH010-05 - A Global Analysis of the Effects of Hydrometeorological Variables on Human Leptospirosis Incidence" |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Other audiences |
Results and Impact | Presentation of virtual poster in an hour-long session titled "GH010 - Impacts of Climate on Vector-Borne and Other Environmental Infectious Diseases eLightning" with other researchers, followed by discussion and question and answer. In addition to the research findings, the UnderWRiDE project was mentioned and the presentation pointed to the website. Afterwards there was a one-on-one discussion with one of the other presenters. |
Year(s) Of Engagement Activity | 2020 |
URL | https://agu.confex.com/agu/fm20/meetingapp.cgi/Paper/673449 |
Description | Poster presentation at the AGU Fall Meeting 2021: "Leptospirosis Prediction Modelling Under Hydrometeorological Extremes Using Random Forest Machine Learning: a Case Study of the Flood Prone Northeastern Districts of Peninsular Malaysia" |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Postgraduate students |
Results and Impact | Presentation in the form of a poster on a new classification model for leptospirosis incidence based on hydrometeorological variables and their extremes, at the AGU Fall Meeting 2021. |
Year(s) Of Engagement Activity | 2021 |
URL | https://agu.confex.com/agu/fm21/meetingapp.cgi/Paper/924542 |
Description | Presentation at AGU Fall Meeting 2022: 'Understanding and managing the risk of water-related diseases under hydrometeorological extremes' |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Postgraduate students |
Results and Impact | Zulkafli, Z., Rahmat, F., Jayaramu, J. Ishak, A.J., Abdul Rahman, R.Z., Ab Rahman, J. De Stercke, S., Mijic, A. Templeton, M.R., and Buytaert, W., 2022, 'Understanding and managing the risk of water-related diseases under hydrometeorological extremes', paper presented at the AGU Fall Meeting 2022, Chicago, 12-16 December 2022. |
Year(s) Of Engagement Activity | 2022 |
Description | Presentation to MSc Environmental Management in Developing Countries |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | Local |
Primary Audience | Postgraduate students |
Results and Impact | Presentation of my research on the water-energy nexus of Mumbai, and on leptospirosis in Malaysia and developing countries, to students of Imperial College London's MSc in Environmental Engineering as well as to other more senior presenters. |
Year(s) Of Engagement Activity | 2022 |
Description | Progress update presentation to the Malaysian Ministry of Education |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | National |
Primary Audience | Policymakers/politicians |
Results and Impact | Comprehensive progress update to the Malaysian Ministry of Education by the UPM researchers. |
Year(s) Of Engagement Activity | 2020 |
Description | Project website with periodic updates about the project and contact information. |
Form Of Engagement Activity | Engagement focused website, blog or social media channel |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Other audiences |
Results and Impact | We created a website in 2020 for anyone to learn more about UnderWRiDE and to keep up to date with progress made. It was only launched in the second half of 2020, and had 83 visitors. |
Year(s) Of Engagement Activity | 2020 |
URL | http://bit.ly/underwride |