Indian Journal of Animal Research

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Research Article

Indian Journal of Animal Research, volume 57 issue 9 (september 2023) : 1221-1226

Estimating Heterogeneity and Pooled Prevalence of Classical Swine Fever in Pigs in India: A Meta-analysis

P. Prema1, Y.C. Bangar2, Vijay Bahadur Sharma1, Sanjay Kumar1, Dinesh Kumar1, Med Ram Verma1,*
1Division of Livestock Economics, Statistics and Information Technology, ICAR-Indian Veterinary Research Institute, Izatnagar, Bareilly-243 122, Uttar Pradesh, India.
2Department of Animal Genetics and Breeding, Lala Lajpat Rai University of Veterinary and Animal Sciences, Hisar-125 001, Haryana, India.
Cite article:- Prema P., Bangar Y.C., Sharma Bahadur Vijay, Kumar Sanjay, Kumar Dinesh, Verma Ram Med (2023). Estimating Heterogeneity and Pooled Prevalence of Classical Swine Fever in Pigs in India: A Meta-analysis . Indian Journal of Animal Research. 57(9): 1221-1226. doi: 10.18805/IJAR.B-4374.

ABSTRACT

Background: Classical swine fever (CSF) is caused by small enveloped RNA virus that belongs to the Flaviviridae family and causes high morbidity and mortality events for pig farming. In India, it is highly prevalent but with varied distribution in various geographical areas resulting in substantial economic losses to farmers. The discrepancy in prevalence estimates across studies needs to be evaluated in order to strengthen the prevention and control strategies of CSF in pigs. The aim of the present study was to provide the pooled estimate of the prevalence of classical swine fever (CSF) in India and to examine the consistency of those estimates between published studies.

Methods: The data regarding prevalence of CSF in 7045 pigs were compiled from 22 published studies using comprehensive literature search for period from 1998 to 2018. The pooled prevalence of CSF was obtained under random effects model and heterogeneity between studies was determined using I² Index. Representation of meta-analysis was done using forest plot and followed by funnel plot, Baujat plot and radial plot.

Result: The result of Meta-analysis revealed that pooled estimate of prevalence of CSF under random effects model was 45% (95% confidence interval: 35, 55%) in India. The heterogeneity statistic (Q) was found to be significant (p<0.001) with I² = 98% which indicated that prevalence of CSF was inconsistent between the studies. Likewise, results of funnel plot and Radial plot indicated heterogeneity between studies. Most influential studies for overall heterogeneity were identified using Baujat and radical plots.

INTRODUCTION

Classical swine fever (CSF), also known as ‘Hog Cholera’ is an OIE List A disease causing vast economic losses to pig farming all over the countries worldwide (Anonymous, 2020). It is caused by a small enveloped RNA virus which belongs to the family Flaviviridae and genus Pestivirus (Wengler et al., 1995). The transmission of virus happens through saliva, urine and faeces of infected animals (Depner et al., 1996). It affects animal with more severity and causing high mortality (Lalremruata et al., 2015). Singh et al., (2016) estimated high annual economic losses (Rs. 4.3 billion) in pigs using sample survey data of India.

In India, the pig population is 9.06 million as per 20th national livestock census (2019) which decreased about 12% as compared to 19th livestock census (2012). The exotic/ crossbred pigs contribute about 21% of the total pig population, while 79% population belongs to indigenous/non-descript category. The disease is endemic in India due to its high prevalence among pig population. The first appearance of CSF was reported in India in 1944 (Krishnamurty et al., 1962). This disease shows acute, chronic or inapparent form (Rout et al., 2015). Over the decades, several authors reported high incidences of disease in different states of India (Nandi et al., 2011; Deori et al., 2012; Ahuja et al., 2014; Choori et al., 2015; Mukherjee et al., 2018). The findings reported earlier showed discrepancies may be due to discrepancy between location, period and sample size of the studies.

In order to reconcile these findings, systematic approach is of utmost necessity in order to provide a reliable estimate of the disease. Meta-analysis combines the results from multiple studies and offers generalize and more reliable conclusions (Walker et al., 2008). It also highlights the causes of variations present in studies, increases precision and provides insights for future hypotheses.

The purpose of the present study was to obtain pooled estimates of CSF prevalence in pigs by employing meta-analysis technique. Further, the heterogeneity amongst the studies was also to be examined.

MATERIALS AND METHODS

Literature search
 
Systematic review of prevalence of CSF in India was carried out by using published studies for a period of 21 years from 1998 to 2018 from various journals and online search engines like PubMed, Science Direct, Google scholar, NCBI, J-Gate, Krishikosh, etc. All references in these studies were cross examined to find additional research papers not included in previous searches.
 
Data sources and study selection
 
A set inclusion criterion for selection of studies have been made on the basis of study objectives that required information such as author, year, location, period of study, total sample size and positive number per study. Studies regarding prevalence of CSF in India were extracted in Indian Scenario and flow diagram of selection of studies used in meta-analysis is presented in Fig 1. Out of total 73 studies, 39 studies were irrelevant as prevalence was not reported for India. Although the data of 44 studies were expected, however, 22 studies were inadequate due to lack of information on the prevalence of CSF. Finally, 22 studies were included in meta-analysis (Table 1).

Fig 1: Flow diagram of study selection in the meta-analysis of CSF fever in India.



Table 1: List of 22 studies included in the meta-analysis.


 
Meta-analysis
 
Random effects model was employed to obtain pooled estimates of CSF prevalence (Higgins and Thompson, 2002; Borenstein, 2009). The Statistic Q was used to test the heterogeneity between studies (Cochran, 1954) and further, Higgins’s I² Index was employed to quantify percent heterogeneity (Higgins et al., 2003).

Graphical representation of meta-analysis was done using forest plot. Further, funnel plot was used for bias or systematic heterogeneity, which provides funnel shaped distribution of studies in absence of bias (Light and Pillemer 1984). Baujat plot and radical plots were also used to detect sources of heterogeneity in meta-analysis (Galbraith 1988; Baujat et al., 2002). Baujat plot provides the influence of each study for the overall heterogeneity. Radical plot displays several estimates of the same quantity that have different standard error. Meta-analysis was performed by using “R” software (https://www.R-project.org/).

RESULTS AND DISCUSSION

Meta-analysis of CSF prevalence was carried out by using total 22 published studies of India comprising data of 7045 pigs. The details of studies included and the results of meta-analysis are shown on forest plot (Fig 2). The results showed pooled estimate of CSF was 45% (95%CI: 0.35; 0.54). Q statistics was found to be significant (Q=926.03; df=21, p<0.001) and it was concluded that there was significant heterogeneity between the studies. Between studies variance (tau-square) was 0.79. Heterogeneity across studies was quantified by I2 Index (98%).

Fig 2: Forest plot showing meta-analysis of prevalence of CSF in India using total 22 published studies.



Funnel plot shows that there is little deviation from this shape which indicated that publication bias was less (Fig 3). Baujat plot showed that studies located in the upper right corner of the graph were most influential ones with the highest contribution to the overall heterogeneity (Fig 4). Among all studies used, Rout et al., (2012), Nandi et al., (2011), Kataria et al., (2010), Mukherjee et al., (2018) and Rajbongshi et al., (2015) studies had higher contribution to overall heterogeneity. Likewise, Radial plot showed that there was greater heterogeneity in the meta-analysis studies (Fig 5).

Fig 3: Funnel plot for prevalence of CSF in pigs in India using total 22 published studies.



Fig 4: Baujat plot for prevalence of CSF in pigs in India using total 22 published studies.



Fig 5: Radial plot for prevalence of CSF in pigs in India using total 22 published studies.



The present estimate of prevalence of CSF was lower than findings of Singh et al., (2016) who reported 61.58% in India. However, our estimate was higher than findings reported by Patil et al., (2018) who provided lower pooled estimate as 37% (95% confidence interval [CI]=0.24, 0.51) of CSF in pigs under meta-analysis using data of 5 years (2011-15). This discrepancy could be due to a higher sample size (7045 pigs) included in our meta-analysis as compared to sample size (6158 pigs) in meta-analysis of Patil et al., (2018). Further, the present estimate of prevalence of CSF was lower than estimate given by Li et al., (2018) in Tibetan pigs in Nyingchi, Tibet China.

Our meta-analysis was different from the previous meta-analysis performed by Patil et al., (2018) in a number of respects: (i) we used larger sample size in meta-analysis (ii) our study period was larger (iii) we used Baujat plot to identify influence of each study to inconsistency in results (iv) we used radial plot to estimate standardized scores.

The present meta-analysis was undertaken in Indian scenario to obtain the pooled prevalence of CSF in pigs and we compared our results with some Indian authors who reported prevalence of CSF using published reports or studies. However, literature on CSF in exotic pigs lacks information on prevalence of CSF which hinders any comparison of our results with exotic pigs.

CONCLUSION

The present meta-analysis was undertaken estimate pooled CSF prevalence in pigs in India using 22 published studies over 21 years. The pooled prevalence was observed as 45%, which indicated that this disease is of high importance in studied population. We also found that there was high heterogeneity between studies and those with high contribution were identified.

ACKNOWLEDGEMENT

The authors are thankful to the Director, ICAR-Indian Veterinary Research Institute, Izatnagar, Bareilly, Uttar Pradesh, India for providing necessary facilities to conduct the study. The authors also express their gratitude to the learned referee and the Editor for their valuable comments on the original version of the paper.

DISCLOSURE STATEMENT

 No potential conflict of interest was reported by the authors.

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