the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 17 Feb 2026
Quantifying Compounded Economic Impacts and Disease Burden of Flooding in Can Tho, Vietnam
Abstract. In growing urban areas, floods increasingly threaten daily life, causing economic losses and raising public health burdens through microbial exposure. Yet, risk assessments often treat economic and health impacts separately, overlooking their interconnected nature and potentially biasing adaptation strategies. This study addresses this gap by quantifying spatial and distributional disparities in flood risks across economic and health dimensions in Can Tho City, a flood-prone urban area in Vietnam’s Mekong Delta.
We calibrate flood impact models for the economic sector by estimating residential building losses, and for the health sector by predicting rotavirus A and E. coli concentrations in floodwaters and resulting disease burden. By combining probabilistic flood simulations with exposure data, we develop a multi-risk framework to capture co-occurring economic and health impacts. Economic risk is quantified via Value at Risk (VaR) and Expected Annual Damage (EAD) for fluvial–pluvial flooding, while health risk is expressed through the Population Health at Risk (PHaR) and Expected Annual Cases (EAC).
Results show pronounced spatial disparities in intersecting risks. The highest combined economic and health risks are found in Phu Thu and Thuong Thanh wards (Cai Rang district) and An Binh ward (Ninh Kieu district), while An Hoi, An Lac, and Tan An wards (Ninh Kieu district) experience consistently low risks. These findings highlight how urbanization and flooding interact to shape multi-sector vulnerabilities in delta cities.
Competing interests: I am one of the guest editors of the special issue to which the manuscript is submitted.
Publisher's note: Copernicus Publications remains neutral with regard to jurisdictional claims made in the text, published maps, institutional affiliations, or any other geographical representation in this paper. While Copernicus Publications makes every effort to include appropriate place names, the final responsibility lies with the authors. Views expressed in the text are those of the authors and do not necessarily reflect the views of the publisher.- Preprint
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Status: open (until 26 Apr 2026)
- RC1: 'Comment on egusphere-2026-850', Ekbal Hussain, 10 Mar 2026 reply
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RC2: 'Comment on egusphere-2026-850', Carmen Anthonj, 18 Apr 2026
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General comments
Thank you very much for the opportunity to review a paper on Quantifying Compounded Economic Impacts and Disease Burden of Flooding in Can Tho, Vietnam, a topic that is relevant and interesting to the readership of EGUsphere. This manuscript addresses a timely topic and political, as well as societal challenge, and is worthwhile being considered for publication. Yet, major revision, discussion and clarification is needed. One major concern is that while authors claim they integrate economic and health risk modeling, the models seem to treat both separately. This needs to be improved, or the claim needs to be moderated. Also, while the study is limited in several ways, limitations are not mentioned at all. Ethics aren’t either. Below, a list with suggestions is recommended to authors to consider.
Specific comments
Introduction/framing
A clear highlight of the novelty of this manuscript is missing, related to content, approach, etc. Can you please highlight the value and novelty more explicitly? Study rationale, aims and objectives are not fully clear, and differ throughout the manuscript. Please make sure you clearly state what is the aim of this work, incl. the target group considered (children below the age of 5 years old).
While the title prominently suggests to address compounded economic impacts and disease burden of flooding, the links between the two aren’t made explicit enough in the introduction.
The loss and damage literature related to climate change and extreme weather events such as flooding has grown over the past decade, and authors are encourage to refer to relevant frameworks, e.g., Sendai, here, and more explicitly state what are economic, and also, non-economic losses. This is both very relevant for this paper, and it is advised to contextualise results of this research respectively in the discussion section.
Public health risks resulting from flooding are mentioned frequently, yet, what is missing is a mention, consideration, critical discussion of the effects that flooding have on the accessibility to health services and medication. Exposure to infection is one thing, getting ill – and staying ill, another. Accessibility to care, and flood-“disturbed” health seeking behaviour, even if not analysed in this paper, is a very important factor that cannot be omitted.
Methods
Study area description largely lacks contextual information on disease burden overall, economic situation overall (and reliance on aquaculture), flood management in the Vietnamese Mekong Delta, where the Mekong River Commission has been very active to address economic as well as health impacts. Study area description mentions environmental pollution without further specifying, yet, this is very important information in the context of infectious disease exposure.
Data used for this analysis is quite outdated, as it was collected in 2011. Considering the highly dynamic urban population, the fast pace of urbanisation, the increasing frequency and intensity of flooding, as described by authors, this is a major limitation of this study. It needs to be discussed critically in a standalone limitations section.
Focus on building value and expected annual damage seems a little bit simplistic to capture economic risk, as livelihood strategies, assets, occupation, etc, need to be considered as well. It would be good to address this in the discussion and/or limitations section.
Pathogen concentration in flood waters are modelled to appropriate disease risk, but what about household-level drinking water treatment and hygiene behaviour that could mitigate, reduce, eliminate the risk altogether? Authors are encouraged to consider this point in the discussion section, in the limitations, and/or follow up research suggestions.
The multi-risk assessment framework (figure 4) is certainly interesting. How flexible is it to include ad consider additional factors, such as property, health-seeking behaviour or prevention, personal or household behaviour, and drinking water, sanitation and hygiene (WASH)? This would be another important point for discussion.
Exposure data used for this study relies mainly on data on individual buildings, incl. use, cost, structure, type and monetary losses. Isnt also household size a very important factor to consider in the economic impact that the loss of a house could have?
Chapter 2.3.2 notes that the focus of this study are vulnerable populations, namely, children under 5 years old, and seniors older than 65 years old. This comes as a surprise, as it is not introduced in the introduction, an the study design lacks a justification. In the course of study, one of those two target groups (children) is mentioned, but not specified, or discussed. Effects on seniors are not reported at all. Authors are urged to clarify, specify and include respective results related to seniors.
Datasets for this study combine data from 2011 with data from 2018 – in 2026. A reflection on implications on the model results, as well as on the interpretation of the relevance and timeliness would be a valuable addition.
The section on QMRA (2.3.3) notes that “exposure to these (rotavirus A, e. coli) is assumed to occur through accidental ingestion of floodwater. This requires explanation and discussion. What about foodborne exposure, in the absence of sufficient hygiene for the handling of fish and shrimp, for example, as acquaculture is one of the main businesses in the Delta? Also, please note that other waterborne diseases expected in this study area, related to flooding, that also have diarrhoea as symptom, include typhoid fever and cholera. This may deserve a mention also.
Results and discussion
The idea of a discussion section is to contextualise results, and provide a critical reflection with previous work. Please engage more in-depth with previous work to increase credibility of your work, highlight its value, and its shortcomings also, as well as the replicability. Please engage more with the topics opened up in the introduction, and the ones I proposed to consider, beyond that.
Under section 3.3. on intersecting economic risk and disease burden, it does not become clear how and why housing damage, and disease risks in children are used in this study. What makes children more special, susceptible, vulnerable, and why are they used in this analysis and not an different group? Note that children under the age of 5 years old are – globally – the most susceptible to infectious disease related to WASH, incl diarrhoeal diseases (see global burden of disease analyses in the Lancet journals) anyways, regardless of flooding.
What were advantages and disadvantages of models, how are they integrated, and what do we learn? There are a number of discussion points that – from a geoscience, global health, flood impact assessment, and community research perspective are missing, including
- More in-depth engagement with the spatial variation of compounded flood impact
- Consideration of health burden beyond only just infectious disease exposure or physical health impact– as mental and social health are affected too, with tremendous impact on productivity, economic situation,
- Discussion related to mitigation of impact based on healthcare services available and with that, the impact that flooding has on functionality of care, and accessibility, of health facilities, medication (also to be accessed in pharmacies etc). And why this matters from an economic perspective also
- Related to this, a discussion of health inequalities, specific to different population sub-groups – and why children are particularly relevant in this context (or not)
- A discussion around one of the most important livelihoods and economic drivers in the area: aquaculture, and what role it plays in exposure to infectious diseases, and why economic impact of flooding is potentially tremendous beyond housing
- How the results can be used specifically for targeted and improved interventions, also related to the ongoing major efforts of Mekong River Commission and state actors in flood management and mitigation
- Methodological discussions related to the value of this approach, strengths and weaknesses
- Where else could multi-risk assessment framework (figure 4) developed as part of this study be used?
I miss a limitations section, that is really borne from this study. What kind of bias did the design of this study, the choice of models, the age of datasets (that different per factor investigated), the lack of information on spatial extent and spatial and temporal intensity of rainfall during monsoon season, etc., introduce? What would you expect from your analysis had you had access to such data?
Other
Details on ethical considerations, ethics review process, approval, file number of ethics approval and approval date are missing. Please add these. It is expected for health-related research. Should authors have had an exemption from ethics approval, please describe this also.
Citation: https://doi.org/10.5194/egusphere-2026-850-RC2
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- 1
This is a nice paper attempting to merge economic losses from floods using standardised approaches to loss modelling with health impacts due to Rotavirus and E. Coli. The model is built and tested in Can Tho city in Vietnam. Please see my comments and suggestions below.
Major:
Minor:
Abstract: Please can you include more details of your findings in the abstract. The only really finding you mention in there is this sentence “highest combined economic and health risks are found in Phu Thu and Thuong Thanh wards (Cai Rang district) and An Binh ward (Ninh Kieu district), while An Hoi, An Lac, and Tan An wards (Ninh Kieu district) experience consistently low risks”, but it doesn’t say anything quantitative about what these risks are or what lo\w even means.
Introduction: This is too long and much of the basic definition sections can be shortened/removed.
Line 35-37: This sentence needs a reference.
Line 53-54:
Figure 1: The right panel shows the flood inundation map. Is this for a particular event? Or is this the expected inundation hazard? Given that you have rp =100 yr I’m assuming it means inundation hazard. Please be clearer with that the figure is showing, perhaps with a more detailed figure caption. When this figure is referenced in the text you also don’t explain how the hazard was calculated or where it was sourced from.
Supplement 1.1: It’s not clear to me how the cures were determined. Is this a smoothed fit to the histogram? Please also include in the caption what the dotted line indicates.
Equation 2c: I think you are missing a variable in the logit().
Supplement 2.1: I’m afraid I don’t understand the equation setup here. What does the rbloss ~ indicate in this and why are these different to equation 3 in the manuscript?
Lines 241: How was Apel et al., (2016) extended to cover your three districts and how did you refine the spatial resolution n to 5m? Did you rerun those models?
Line 298: can you provide the alpha and beta values for the pathogens that you used. Perhaps in Table 1? Also the unit column in Table 2 is incomplete
Line 318: Typo: D(p) instead of Dp.
Loss results: It’s a little confusing how you present your loss results, e.g. US$1,392.25k. This is too precise given the uncertainties in your data. I would recommend you present the results at a lower precision, e.g. US$1,400k.
Figure 9: I think your EAD and EAC threshold could be cleaner. Consider changing these to lower precision bounds: E.g. EAD: 0-1200; 1200-2400; 2400-3600; 3600-4800. Similarly, for the EAC.