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Multi-sectoral impact assessment during the 1st wave of COVID-19 pandemic in West Bengal (India) for sustainable planning and management

ABSTRACT: With the advancement of globalisation, urbanisation and environmental change, the outbreak of the Coronavirus disease 2019 (COVID-19), as an infectious disease, has become a global threat. The entire world is continuously trying to adapt to the pandemic situation due to the sudden outbreak of COVID-19 and the lockdown phase, which has not been faced before. The fear of infection by such an unknown virus and the epidemic transformed the built-up environment and impacted various sectors of lives and livelihoods, which must be assessed in spatial perspectives. The objective of this research is to assess the multi-sectoral impact due to the COVID-19 pandemic. Thus, it is designed to inspect seven essential sectors, namely, the economy, employment, education, transport, travel and tourism, health and environment sector-wise impact assessment of the West Bengal state of India. Taking the required COVID-19 data from the government website of India (http://www.covid19india.org; https://www.mygov.in/corona-data/covid19-statewise-status) and West Bengal (https://covidindia.org/west-bengal), a methodology is proposed on an integrated framework for the multi-sectoral impact assessment. The study concentrates on West Bengal, as no study exists on the multi-sectoral impact assessment due to the COVID-19 pandemic during the 1st wave, especially using the geospatial platform. The economy, employment, education, transport, health, tourism and environment multi-sectors of West Bengal are selected in this research, as these sectors have built the economic, sociocultural and environmental pillars of the state. All these sectors have been seriously affected, and the nature of the impact is diverse and large. Before the vaccine comes into the hands of the common people of West Bengal and in a broad sense in India, the awareness should be increased at the grass-root level to fight against the pandemic situation and even after the post-COVID era. The application of geospatial technology used for the mapping and analysis of COVID-19 affects the related database to tease out the multidimensional study, which aims to plan future road maps, search for answers and learn to add further security to overcome the future virus attack.

Supplementary Information

The online version contains supplementary material available at 10.1007/s12517-021-08836-z.

SUBMITTER: Mondal B

PROVIDER: S-EPMC8590926 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundPrioritizing zoonotic diseases is one of the emerging tasks for developing multi-sectoral collaboration within One Health. Globally, many efforts have been made to prioritize zoonotic diseases at national levels, especially in low resource settings. Prioritization of zoonoses has been conducted in different countries at different levels (i.e. national, regional and local) for different purposes. India has also initiated prioritization of zoonotic diseases at the national level. However, in a country like India with wide climatic variations, different animal-human and vector densities, it is important to look at these zoonotic conditions in local settings too. The present study aims to determine which zoonoses should be prioritized for collaboration between stakeholders in the Indian city of Ahmedabad.MethodsThe present study followed a participatory research method, entailing a stakeholder workshop for prioritizing zoonotic diseases in Ahmedabad. It was carried out through a facilitated consultative process involving 19 experts in zoonoses from the human and animal health systems during a one-day workshop in September 2018. To prioritize the zoonotic diseases, the One Health Zoonotic Disease Prioritization (OHZDP) tool of the U.S. Centers for Disease Control and Prevention was adopted. The Analytical Hierarchical Process (AHP) and decision-tree analysis were used to rank the diseases.ResultsOut of 38 listed zoonotic diseases, 14 were selected for prioritization. These were scored and weighed against five criteria: severity of disease in humans, potential for epidemic and/or pandemic, availability of prevention and/or control strategies, burden of animal disease existing inter-sectoral collaboration. The top five diseases that have been prioritized for Ahmedabad are Rabies, Brucellosis, Avian Influenza (H5N1), Influenza A (H1N1) and Crimean-Congo Hemorrhagic Fever. Sensitivity analysis did not indicate significant changes in zoonotic disease prioritization based on criteria weights.ConclusionPrioritization of zoonotic diseases at the local level is essential for development of effective One Health strategies. This type of participatory disease prioritization workshop is highly recommended and can be replicated in other Indian cities, as well as in other low and middle-income countries.

Project description:Hybrid rice requires adequate nitrogen (N) management in order to achieve good yields from its vegetative and reproductive development. With this backdrop, a field experiment was conducted at Regional Research Station (Coastal Saline Zone), Bidhan Chandra Krishi Viswavidyalaya, Kakdwip, West Bengal (India) to record growth and yield performance of hybrid rice (cv. PAN 2423) under varied N-fertilizer doses. A modelling approach was adopted for the first time in hybrid rice production system under coastal ecosystem of West Bengal (India). In the present study, the Agricultural Production Systems Simulator (APSIM) model was calibrated and validated for simulating a hybrid rice production system with different N rates. The APSIM based crop simulation model was found to capture the physiological changes of hybrid rice under varied N rates effectively. While studying the relationship between simulated and observed yield data, we observed that the equations developed by APSIM were significant with higher R2 values (≥0.812). However, APSIM caused an over-estimation for calibrate data but it was rectified for validated data. The RMSE of models for all the cases was less than respective SD values and the normalized RMSE values were ≤20%. Hence, it was proved to be a good rationalized modelling and the performance of APSIM was robust. On the contrary, APSIM underestimated the calibrated amount of N (kg ha−1) in storage organ of hybrid rice, which was later rectified in case of validated data. A strong correlation existed between the observed and APSIM-simulated amounts of N in storage organ of hybrid rice (R2 = 0.94** and 0.96** for the calibration and validation data sets, respectively), which indicates the robustness of the APSIM simulation study. Scenario analysis also suggests that the optimal N rate will increase from 160 to 200 kg N ha−1 for the greatest hybrid rice production in coming years under elevated CO2 levels in the atmosphere. The APSIM-Oryza crop model had successfully predicted the variation in aboveground biomass and grain yield of hybrid rice under different climatic conditions.

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Multi-sectoral impact assessment during the 1st wave of COVID-19 pandemic in West Bengal (India) for sustainable planning and management

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