Identify the risk for leptospirosis disease during flooding periods (Special reference to Medirigiriya Divisional Secretariat Division in Polonnaruwa district).

Wijerathne, K.B.P.C.A.; Senevirathna, E.M.T.K.

doi:10.1016/j.proeng.2018.01.014

Cited by 6 publications

(7 citation statements)

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“…Table 2 provides characteristics of these included studies. A summary of the thirty-one studies [5,7,13,35–62] are provided in S3 Table.…”

Section: Resultsmentioning

confidence: 99%

“…There has been an increased in number of individual studies which assessed the risk of leptospirosis in flood conditions. Some studies showed contact with floods was significantly associated with the occurrence of leptospirosis [11–13], while other studies reported differently [14,15]. In addition to the increased risk of leptospirosis after exposed exposure to flooding, socio-demographic (being male gender) and other predictors like sighting of rats were commonly reported in the individual studies.…”

Section: Introductionmentioning

confidence: 99%

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Risk factors for human leptospirosis following flooding: A meta-analysis of observational studies

et al. 2019

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Leptospirosis is probably the most widespread zoonotic disease in the world especially in tropical countries. There has been an increase in individual studies, which assessed the frequency of leptospirosis in flood conditions. Some studies showed contact with floods was significantly associated with the occurrence of leptospirosis while other studies reported differently. The objective of this meta-analysis was to synthesize the evidence on the risk factors which are associated with human leptospirosis following flooding. We set up the inclusion criteria and searched for the original studies, addressing leptospirosis in human with related to flood in health-related electronic databases including PubMed, Embase, Ovid Medline, google scholar and Scopus sources. We used the terms ‘leptospirosis’, ‘flood’, ‘risk factor’ and terms from the categories were connected with “OR” within each category and by “AND” between categories. The initial search yielded 557 citations. After the title and abstract screening, 49 full-text papers were reviewed and a final of 18 observational studies met the pre-specified inclusion criteria. Overall, the pooled estimates of 14 studies showed that the contact with flooding was a significant factor for the occurrence of leptospirosis (pooled OR: 2.19, 95%CI: 1.48–3.24, I 2 :86%). On stratification, the strength of association was greater in the case-control studies (pooled OR: 4.01, 95%CI: 1.26–12.72, I 2 :82%) than other designs (pooled OR:1.77,95%CI:1.18–2.65, I 2 :87%). Three factors such as ‘being male’(pooled OR:2.06, 95%CI:1.29–2.83), the exposure to livestock animals (pooled OR: 1.95, 95%CI:1.26–2.64), the lacerated wound (pooled OR:4.35, 95%CI:3.07–5.64) were the risk factors significantly associated with the incidence of leptospirosis following flooding in the absence of within-study heterogeneity ( I 2 : 0%). We acknowledge study limitations such as publication bias and type 2 statistical errors. We recommended flood control and other environmental modifications that are expected to reduce the risk of leptospiral infection, and a multi-sectoral effort to this aspect would have long-term benefits.

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“…Table 2 provides characteristics of these included studies. A summary of the thirty-one studies [5,7,13,35–62] are provided in S3 Table.…”

Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Risk factors for human leptospirosis following flooding: A meta-analysis of observational studies

et al. 2019

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“…These rainfall increments are interesting for further analysis. However, Polonnaruwa has a plain terrain and floods are frequent (Wijerathne and Senevirathna, 2018). These floods usually damage the paddy harvest.…”

Section: Case Study Application To North West and North Central Provincesmentioning

confidence: 99%

Analyzing relationships between rainfall and paddy harvest using artificial neural network (ANN) approach: case studies from North-western and North-central provinces, Sri Lanka

et al. 2022

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Purpose: Food and agriculture are frequently affected from on-going climate change. A significant percentage of annual harvest is lost due to extreme climatic conditions in different parts of the world. Sri Lanka is considered as a country which is vulnerable to climate change. Therefore, this research presents a detailed analysis to find out the non-linear relationships between the rainfall and paddy harvest in two major provinces of Sri Lanka.Research Method: North-central and North-western provinces as two major agricultural areas were selected for the study. Rainfall trends were identified using non-parametric Mann-Kendall and Sen's slope estimator tests. The artificial neural network (ANN) approach was used to establish non-linear relationships between rainfall and paddy yield.Findings: There was no significant (p > 0.05) linear correlation between rainfall amount and the rainfed paddy yield in tested locations. However, no clear relationship between the rainfall and rain fed yield were found in the 14 predefined functions (polynomial, logarithmic, exponential and trigonometric) derived using ANN where the calculated coefficients of determination were less than 0.3. Research Limitations:Due to lack of other climate variables such as temperatures, a significant relationship was not observed in this study. Originality/value:We have shown that non-linear artificial neural network approach can be used to study the impact of climate on agricultural production in Sri Lanka.

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“…In addition to damage caused by the direct water impact, water's energy works as an erosive agent [14] that may undermine materials under the foundations of buildings, causing them to collapse [15]. Once the flood is over, damage may continue to increase due to electricity and water cutoffs or the spread of diseases such as cholera, leptospirosis, and typhoid fever [16][17][18], increasing economic and personal losses in the affected area [19]. Despite the natural origin of these floods, the main reason for damage can be identified in the human occupation of areas traditionally susceptible to flooding [20,21].…”

Section: Introductionmentioning

confidence: 99%

Social Vulnerability Assessment for Flood Risk Analysis

Tascón-González

Ferrer-Juliá

Ruiz

et al. 2020

Water

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This paper proposes a methodology for the analysis of social vulnerability to floods based on the integration and weighting of a range of exposure and resistance (coping capacity) indicators. It focuses on the selection and characteristics of each proposed indicator and the integration procedure based on the analytic hierarchy process (AHP) on a large scale. The majority of data used for the calculation of the indicators comes from open public data sources, which allows the replicability of the method in any area where the same data are available. To demonstrate the feasibility of the method, a study case is presented. The flood social vulnerability assessment focuses on the municipality of Ponferrada (Spain), a medium-sized town that has high exposure to floods due to potential breakage of the dam located upstream. A detailed mapping of the social vulnerability index is generated at the urban parcel scale, which shows an affected population of 34,941 inhabitants. The capability of working with such detailed units of analysis for an entire medium-sized town provides a valuable tool to support flood risk planning and management.

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Identify the risk for leptospirosis disease during flooding periods (Special reference to Medirigiriya Divisional Secretariat Division in Polonnaruwa district).

Cited by 6 publications

References 1 publication

Risk factors for human leptospirosis following flooding: A meta-analysis of observational studies

Risk factors for human leptospirosis following flooding: A meta-analysis of observational studies

Analyzing relationships between rainfall and paddy harvest using artificial neural network (ANN) approach: case studies from North-western and North-central provinces, Sri Lanka

Social Vulnerability Assessment for Flood Risk Analysis

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