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. 2024 Aug 29;44(1):1–18. doi: 10.1080/01652176.2024.2396577

The global seroprevalence of Toxoplasma gondii infection in workers occupationally exposed to animals (1972–2023): a systematic review and meta-analysis

Abdullah Mohammed a,✉, Musa Ahmed b, Nasir Ibrahim c
PMCID: PMC11363739  PMID: 39205625

Abstract

Toxoplasma gondii, a ubiquitous zoonotic parasite infecting warm-blooded animals, poses a significant health threat to workers with occupational animal exposure (WOEA) due to their frequent contact with potential reservoirs. Existing data on T. gondii seroprevalence in the WOEA exhibits substantial global variation. This systematic review and meta-analysis, adhering to PRISMA guidelines, aimed to quantify the global seroprevalence of T. gondii infection among WOEA over the past five decades (1972–2023). We identified 66 eligible studies through a comprehensive search strategy encompassing English publications, with a total sample size of 15,279. A random-effects model with the Freeman-Tukey transformation in STATA v16.0 accounted for the high heterogeneity observed. We estimated the pooled global seroprevalence of T. gondii infection in WOEA at 41% (95% CI: 36–47%). Subgroup analyses revealed significant variations by gender: males (63%) vs. females (37%) (p < 0.05), occupation: non-livestock workers (54%), livestock workers (47%), slaughterhouse workers (44%), and veterinary personnel (27%) (p < 0.05). Geographic trends showed the highest prevalence in Africa (51%), followed by South America (49%), Europe (47%), Australia (43%), Asia (36%), and North America (23%; p < 0.05). Lower prevalence was observed in high-income (39%) and upper-middle-income (38%) countries compared to lower-middle-income (44%) and low-income (48%) countries (p < 0.05). This analysis underscores the high global seroprevalence of T. gondii in the WOEA, highlighting the need for targeted interventions in this high-risk population.

Keywords: Toxoplasma gondii, seroprevalence, workers occupational exposure to animals, systematic review, meta-analysis, zoonosis

1. Introduction

Toxoplasma gondii is an obligate intracellular parasite that infects virtually all warm-blooded animals, including humans (Tenter et al. 2000). Infection with T. gondii can cause a disease called toxoplasmosis, which can be severe and even fatal in some cases, particularly in neonates and immunocompromised individuals (Saadatnia and Golkar 2012; Wang et al. 2017). Toxoplasmosis is a major public health concern worldwide, with approximately 2 billion people infected (Rahmanian et al. 2020). The majority of infected people are asymptomatic, but some may experience mild flu-like symptoms. In severe cases, toxoplasmosis can cause a variety of complications, including encephalitis, retinitis, and seizures (Saadatnia and Golkar 2012).

Workers occupationally exposed to animals (WOEA), such as animal breeders, hunters, butchers, livestock workers, meatpacking workers, slaughterhouse workers, and veterinary personnel, are at heightened risk of T. gondii infection, particularly if they do not use appropriate personal protective equipment (PPE) (Wright et al. 2008; Odo et al. 2015; Habib and Alshehhi 2021). This is because many animals, including cattle, sheep, goats, camels, pigs, and chickens, can harbor the parasite (Belluco et al. 2016; Abdullah et al. 2022). WOEA can be exposed to the parasite through direct contact with infected animals or their bodily fluids, indirect contact with contaminated surfaces or objects, or accidental ingestion of raw or undercooked meat (Tenter et al. 2000).

The prevalence of T. gondii infection in WOEA varies widely around the world, ranging from 4.8% in a study from the United States (Rosypal et al. 2015) to 96.3% in a study from Ghana (Abu et al. 2015). This is likely due to a number of factors, including the type of animals that workers are exposed to, the level of hygiene in the workplace, and the prevalence of T. gondii infection in the animal population.

The global seroprevalence of T. gondii infection in WOEA is not well known. To date, there has been no systematic review or meta-analysis that has investigated the global seroprevalence of T. gondii infection in WOEA. The aim of this systematic review and meta-analysis is to estimate the global seroprevalence of T. gondii infection in WOEA during the last five decades, from 1972 to 2023. The findings of this review will provide valuable information to policymakers and healthcare professionals about the burden of T. gondii infection in WOEA.

2. Materials and methods

2.1. Study design and protocol registration

This meta-analysis adhered to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines (Page et al. 2021). The study protocol was prospectively registered in the International Prospective Register of Systematic Reviews (No. CRD42023412590).

2.2. Eligibility criteria

The full eligibility criteria used to determine studies for inclusion in the current analysis are displayed in Table 1. In addition to the criteria listed in the table, reviews, letters, editorials, and studies without full-text availability or that did not report the information needed to meet the eligibility criteria were excluded. Furthermore, studies with missing information were excluded after the primary investigator (AM) attempted to contact the corresponding author(s) via email and/or ResearchGate personal pages to obtain the original data but failed to obtain the missing information within 4 weeks.

Table 1.

Study inclusion/exclusion criteria.

Inclusion Exclusion
Studies that reported the seroprevalence of T. gondii infection in workers occupationally exposed to animals, including those in the following groups: livestock workers, non-livestock workers, slaughterhouse workers, fishermen, and veterinary personnel in any part of the world Studies that did not report the seroprevalence of T. gondii infection in workers occupationally exposed to animals or reported it in other groups
All observational studies Studies that were not observational in nature
Use of a validated serological test to diagnose T. gondii infection as described by Khan and Noordin (2020) Studies that did not use a validated serological test to diagnose T. gondii infection
In English Language limitation: Not in English
Full text of publication obtained Full text unavailable
Studies that provided sufficient information on sample size, sampling location, or sampling period Studies that did not provide sufficient information on sample size, sampling location, or sampling period
  Other
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2.3. Information sources

Information relevant to the current systematic review was searched for and identified by two investigators, Abdullah Mohammed (AM) and Musa Ahmed (MA), who conducted separate searches in research databases (Table 2) from their inception to October 15, 2023, for studies on the seroprevalence of T. gondii infection in workers occupationally exposed to animals, published in English. In addition to the electronic databases and grey literature sources, the authors also searched the reference lists of relevant studies for additional eligible studies.

Table 2.

Databases searched and number of hits.

Database Website No. hits
Scopus https://www.scopus.com/ 71
Web of Science https://www.webofscience.com/wos/ 42
PubMed https://pubmed.ncbi.nlm.nih.gov/ 268
Google Scholar@ https://scholar.google.com/ 317
ResearchGate@ https://www.researchgate.net/ 197
Semantic Scholar@ https://www.semanticscholar.org/ 68
African Journals Online (AJOL) https://www.ajol.info/index.php/ajol 338
Scientific Electronic Library Online (SciELO) https://www.scielo.org/ 15
World cat https://www.worldcat.org/ 108
ProQuest Dissertations and Theses https://www.proquest.com/ 56
Total 1480
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Note: @ Google Scholar, Semantic Scholar, and ResearchGate were used as supplementary sources for additional relevant studies but are not listed as primary databases.

2.4. Search strategy and data items

The search strategy was developed in consultation with a medical librarian and tailored to each database (Table 2). The strategy aimed to identify studies that investigated the seroprevalence of T. gondii infection in workers occupationally exposed to animals. It employed Boolean search terms (AND, OR, NOT) and included keywords focusing on titles and abstracts related to T. gondii infection (Toxoplasmosis, Toxoplasma gondii, T. gondii, and Toxoplasma), workers occupationally exposed to animals (abattoir workers, animal attendants, animal handlers, animal hunters, animal hospital workers, animal technicians, butchers, dairy farmers, fishermen, fish farm workers, food animal workers, laboratory animal workers, livestock workers, meatpacking workers, slaughterhouse workers, veterinarians, veterinary pharmacists, veterinary students, and veterinary technicians), and seroprevalence (epidemiology, frequency, prevalence, risk factors, seroprevalence, and surveillance). The search covered studies published between 1972 and 2023.

2.5. Study selection process and risk of bias assessment

The selection process of studies in the current analysis was guided by the PRISMA statement (Figure 1) and the abovementioned inclusion and exclusion criteria, and the following order was followed: Firstly, all selected electronic databases were screened by two independent reviewers (AM and MA) to identify and retrieve eligible studies; any disagreements during this phase between them were resolved by discussion; and the agreed studies were then exported to version X9.3.3 of the EndNote citation manager to identify and remove duplicated studies. Next, the two reviewers independently screened the titles and abstracts of all remaining studies to identify those that potentially met the inclusion criteria, and any disagreements during this phase were resolved in consultation with a third reviewer. The full text of all potentially eligible studies was then retrieved and reviewed to confirm eligibility. Subsequently, the remaining studies were subjected to additional quality checks using the Joanna Briggs Institute (JBI) critical appraisal checklist for observational studies (Jordan et al. 2019). Finally, the inter-rater agreement between AM and MA was measured using Cohen’s Kappa statistic, which achieved a value of 1, indicating perfect agreement (Gwet 2008). All studies that met the inclusion criteria of the review were selected for inclusion in the meta-analysis.

Figure 1.

Figure 1.

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Flowchart of study inclusion and exclusion for the meta-analysis of T. gondii seroprevalence in WOEA.

2.6. Data collection process

Data were collected from the full text of all eligible studies. Two independent reviewers, AM and MA, extracted data from each study using a standardized data extraction form based on the objectives of the review and the Joanna Briggs Institute data extraction tool for systematic reviews. The data extraction form included items (Table 2) related to:

  • Study characteristics: author(s), study period and year of publication, study design, continent, country, and World Bank income category, which was based on the most recent World Bank income classification system that was used to categorize the participating countries based on their Gross National Income (GNI) per capita (World Bank Country and Lending Groups 2024).

  • Study participant characteristics: sample size, age, gender, and occupation of participants.

  • Exposure assessment: Methods used in each study to assess participant exposure to T. gondii.

  • Outcome assessment: methods used in each study to diagnose T. gondii infection.

  • Results: prevalence of T. gondii infection.

The two reviewers worked independently to extract data from each study. However, any discrepancies in the data extraction were resolved through discussion or by consultation with a third reviewer. In addition, if the reviewers had any questions about the data extracted from a study, they contacted the corresponding author of the study via email and/or ResearchGate personal pages to obtain or confirm the data. Finally, to ensure accuracy, a pilot test was performed on 20 randomly selected papers (30% of the total) by comparing the data extraction results of two reviewers, AM and MA. This helped identify any inconsistencies in the data extraction process and make necessary revisions to the data extraction template.

2.7. Synthesis methods

The results of the individual studies were synthesized and analyzed using Stata software version 16.0 and a random-effects model with a statistical significance level of p < 0.05.

The subsequent analysis required two statistical measurements: effect size (ES) with a 95% confidence interval (CI) and standard error (SE). Whereby, ES was calculated using the binomial distribution and the prevalence of T. gondii infection in workers occupationally exposed to animals (proportion), and SE was calculated using the following formula:

SE=sqrt(p(1−p)/n)

where

p is the proportion of T. gondii infection-positive cases in the overall population of workers who are occupationally exposed to animals.

n is the sample size.

To stabilize the variance, the Freeman-Tukey double arcsine transformation (PFT) was used before meta-analysis to make the rate more consistent with the Gaussian distribution (Mia et al. 2022; Mohammed et al. 2023).

Additionally, the presence and extent of statistical heterogeneity were assessed using the Cochran’s Q test and the I2 statistic. If the Cochran’s Q test was significant (p < 0.10) or the I2 statistic was greater than 50% (Higgins et al. 2003), this was considered to be evidence of statistical heterogeneity.

The present heterogeneity was explored by subgroup analyses and meta-regression to identify the possible causes of heterogeneity among study results. This involved dividing the studies in the meta-analysis into subgroups based on different characteristics, such as study design, participant characteristics, and exposure assessment, and checking the possible relationship between study variables and the prevalence of human toxoplasmosis by the meta-regression test (univariate and multivariate regression).

Furthermore, a sensitivity analysis was conducted to assess the robustness of the synthesized results by repeating the meta-analysis with different assumptions or criteria, such as excluding studies that were rated as having a ‘high’ or ‘moderate’ risk of bias.

In addition, to check for potential publication bias, the visual symmetry of the funnel plot and the result of the regression-based Egger test were used. The Egger test was considered significant if the P values were less than 0.10.

Overall, the results of the final meta-analysis model were presented as forest plots, which included the results of each individual study as well as the pooled results of all included studies.

3. Results

3.1. Study identification and selection

A comprehensive search strategy was employed to identify relevant studies. Electronic databases were systematically searched, yielding a total of 1480 potentially eligible studies (Table 2). Following a rigorous screening process based on pre-defined inclusion and exclusion criteria, a substantial number of studies (n = 1005) were excluded (Figure 1). Duplicates (n = 375) were removed using reference management software (EndNote version X9.3.3). An additional 583 studies were excluded for not meeting the eligibility criteria established a priori. These criteria centered on specific aspects of study design (e.g. intervention type, study population), methodological quality, and outcome measures.

The remaining 475 studies proceeded to full-text assessment for a more in-depth evaluation. Following a meticulous review process, 214 studies were excluded for various reasons. These included:

  • Insufficient data for analysis (n = 22)

  • Poor methodological quality as assessed by established quality appraisal tools (n = 93)

  • Language barriers (studies published in languages other than English, n = 41)

  • Reporting on the same study population in multiple publications (n = 19)

  • Sample size less than 30 participants (n = 4)

Concurrent with the database search, a citation search of the retrieved studies identified 57 potentially relevant articles. However, 27 were excluded due to non-retrieval. The remaining 30 articles underwent full-text screening using the same stringent criteria applied to database studies. This process resulted in the exclusion of an additional 27 articles.

Ultimately, following a rigorous selection process, 66 studies were deemed eligible for inclusion in the final quantitative and qualitative synthesis. Of these, 59 originated from the initial database search, and 7 were identified through the citation search of retrieved studies.

3.2. Study characteristics

The key characteristics of the 66 studies included in this meta-analysis are summarized in Table 3. All continents were represented, with studies originating from Africa (n = 17, 25.8%), Asia (n = 22, 33.3%), Australia (n = 1, 1.5%), Europe (n = 9, 13.6%), North America (n = 9, 13.6%), and South America (n = 9, 13.6%). The World Bank income classifications were also well represented, with studies from high-income (n = 22, 33.3%), upper-middle-income (n = 17, 25.8%), lower-middle-income (n = 21, 31.8%), and low-income (n = 7, 10.6%) countries.

Table 3.

Participant and main study characteristics of included studies.

Continent Country/income classification Study author Period of study Study design Diagnostic method Study participants occupation Age (years) Sample size
 Seroprevalence, n (%)
Overall Male Female Overall Male Female
Africa Central African Republic/LIC Bouscaren et al. (2018) November 2011–December 2012. CS ELISA Livestock workers 65–80 409 NR NR 263 (64.3) NR NR
Egypt/LMIC Barakat et al. (2011) NR CS IFAT Livestock workers NR 127 NR NR 48 (37.8) NR NR
Egypt/LMIC Elsheikha et al. (2009) March–September 2007 CS ELISA Livestock workers, slaughterhouse workers, and veterinary personnel 20–50 109 NR NR 77 (70.6) NR NR
Ghana/LMIC Abu et al. (2015) NR CS ELISA Non-livestock workers 10–100 81 NR NR 78 (96.3) NR NR
Kenya/LMIC Cook et al. (2021) NR CS ELISA Slaughterhouse workers 18–85 738 711 26 619 (84) 601 (97.1) 18 (2.9)
Kenya/LMIC Thiong’o et al. (2016) March–June 2013 CS PCR Slaughterhouse workers NR 87 NA NA 34 (39.1) NA NA
Namibia/UMIC Colf et al. (2014) October 2011–January 2012 CS ELISA Livestock workers, slaughterhouse workers, and veterinary personnel 20–50 100 NR NR 32 (32) NR NR
Nigeria/LMIC Abraham et al. (2021) May 2016–July 2017 CS ELISA Livestock workers and slaughterhouse workers 15–78 339 283 56 189 (55.8) 151 (79.9) 38 (20.1)
Nigeria/LMIC Alayande et al. (2012) NR CS LAT Slaughterhouse workers 11–60 75 NR NR 20 (26.7) NR NR
Nigeria/LMIC Kamani et al. (2009) February–May 2008 CS ELISA Livestock workers NR 40 NR NR 13 (32.5) NR NR
Republic of Congo/LIC Bouscaren et al. (2018) November 2011–December 2012. CS ELISA Livestock workers 65–80 408 NR NR 224 (54.9) NR NR
Sudan/LIC Musa (2021) 2020–2021 CS LAT Livestock workers NR 99 NR NR 40 (40.4) NR NR
Slaughterhouse workers NR 16 NR NR 7 (43.8) NR NR
Veterinary personnel NR 5 NR NR 0 NR NR
Overall 16–68 120 66 54 47 (39.2) 32 (68.1) 15 (31.9)
Sudan/LIC Idris (2021) February 2020–July 2021 CS LAT Livestock workers NR 77 NR NR 37 (48.1) NR NR
Slaughterhouse workers NR 29 NR NR 12 (41.4) NR NR
Veterinary personnel NR 14 NR NR 5 (35.7) NR NR
Overall 6–80 120 78 42 54 (45) 38 (70.4) 16 (29.6)
Sudan/LIC Mohamed (2021) February 2020–July 2021 CS LAT Livestock workers NR 86 NR NR 29 (33.7) NR NR
Slaughterhouse workers NR 21 NR NR 13 (61.9) NR NR
Veterinary personnel NR 13 NR NR 9 (69.2) NR NR
Overall 1–100 120 56 64 51 (42.5) 27 (52.9) 24 (47.1)
Sudan/LIC Ahmed (2021) February 2020–September 2021 CS LAT Livestock workers NR 105 NR NR 84 (80) NR NR
Slaughterhouse workers NR 6 NR NR 4 (66.7) NR NR
Veterinary personnel NR 9 NR NR 8 (88.9) NR NR
Overall 1–80 120 30 90 96 (80) 27 (28.1) 69 (71.9)
Sudan/LIC Alshaeb (2017) November 2017 CC LAT Slaughterhouse workers & veterinarians NR 70 NA NA 8 (11.4) NA NA
  Tanzania/LMIC Swai and Schoonman (2009) November 2005 CS LAT Livestock workers NR 67 NR NR 35 (52.2) NR NR
Slaughterhouse workers NR 41 NR NR 19 (46.3) NR NR
Non-livestock workers NR 38 NR NR 15 (39.5) NR NR
Veterinary personnel NR 11 NR NR 4 (36.4) NR NR
Overall 14–84 199 132 67 91 (45.7) 62 (68.1) 29 (31.9)
Asia China/UMIC Mao et al. (2021) 2020 CS ELISA Livestock workers, and slaughterhouse workers 16–92 1330 606 724 154 (11.6) 76 (49.4) 78 (50.6)
India/LMIC Deshmukh et al. (2021) 2020 CS ELISA Veterinary personnel NR 139 NR NR 68 (48.9) NR NR
Slaughterhouse workers@ 25–45 126 NR NR 61 (48.4) NR NR
Overall NR 265 NR NR 129 (48.7) NR NR
India/LMIC Thakur et al. (2022) 2017–18 CS ELISA Veterinary personnel 21–60 205 NR NR 18 (9) NR NR
India/LMIC Rahman et al. (2008) 2004–2005 CS ELISA Veterinary personnel NR 78 NR NR 8 (10.3) NR NR
Iraq/UMIC Al-Imara and Thamir (2009) NR CS LAT Slaughterhouse workers 20–50 100 NR NR 47 (47) NR NR
Iraq/UMIC Omer (2008) 2004–2005 CS LAT Slaughterhouse workers 20–50 79 NR NR 44 (55.7) NR NR
Iran/LMIC Hejazi et al. (2023) 2021 CC ELISA Livestock workers, slaughterhouse workers, and veterinary personnel NR 401 NR NR 185 (46.1) NR NR
Iran/LMIC Beheshtipour et al. (2019) May–October 2018 CS ELISA Slaughterhouse workers NR 53 NR NR 6 (11.3) NR NR
Iran/LMIC Youssefi et al. (2018) 2016 CS ELISA Slaughterhouse workers NR 91 NR NR 53 (58.2) NR NR
Iran/LMIC Rostami et al. (2016) July 2014–March 2015 CS ELISA Livestock workers NR 57 NR NR 46 (80.7) NR NR
Iran/LMIC Mardani and Tavalla (2015) 2014 CC ELISA Slaughterhouse workers NR 110 NR NR 56 (50.9) NR NR
Iran/LMIC Sadaghian and Jafari (2014) NR CC ELISA Veterinary personnel NR 80 NR NR 27 (33.8) NR NR
Iran/LMIC Shad-Del et al. (1993) NR CS IFAT Livestock workers NR 50 NR NR 14 (28) NR NR
Slaughterhouse workers NR 50 NR NR 17 (34) NR NR
Veterinary personnel NR 50 NR NR 5 (10) NR NR
Overall 18–67 150 NR NR 36 (24) NR NR
Japan/HIC Horio et al. (2001) 1992–1993 CS LAT Slaughterhouse workers 20–60 67 32 35 22 (32.8) 8 (36.4) 14 (63.6)
Malaysia/UMIC Brandon-Mong et al. (2015) October 2013–April 2014 CS ELISA Veterinary personnel 17–64 312 78 234 62 (19.9) 23 (37.1) 39 (62.9)
Malaysia/UMIC Normaznah et al. (2004) NR CS IFAT Livestock workers NR 79 NR NR 22 (27.8) NR NR
Myanmar/LMIC Sint et al. (2023) June–December 2020 CS RDT Slaughterhouse workers 18–66 139 119 20 61 (43.9) 53 (86.9) 8 (13.1)
  Pakistan/LMIC Khan et al. (2022) NR CS ICT Slaughterhouse workers 15–31 270 NR NR 59 (21.9) NR NR
Pakistan/LMIC Anees et al. (2014) NR CS LAT Slaughterhouse workers 51–60 50 NR NR 5 (10) NR NR
Republic of Korea/HIC Sang-Eun et al. (2014) 2009 CS EIA Veterinary personnel 30–60 945 NR NR 76 (8) NR NR
Saudi Arabia/HIC Mohamed et al. (2020) March–April 2019 CS ELISA Slaughterhouse workers 22–61 108 NA NA 27 (25) NA NA
Saudi Arabia/HIC Amin and Morsy (1997) NR CS ELISA Slaughterhouse workers NR 100 NR NR 80 (80) NR NR
Taiwan/HIC Fan et al. (2001) July 1999–June 2000 CS LAT Non-livestock workers 14–60 53 NR NR 28 (52.8) NR NR
Australia New Zealand/HIC Forsyth et al. (2012) 2002–2010 CS ELISA Veterinary personnel & Non-livestock workers NR 88 NR NR 38 (43.2) NR NR
Europe Denmark/HIC Lings et al. (1994) September 1986 CS ELISA Slaughterhouse workers 16–66 217 203 14 98 (45.2) NR NR
Estonia/HIC Lassen et al. (2016) March 2013–January 2014 CS ELISA Livestock workers NR 375 NR NR 281 (74.7) NR NR
October 2012 Veterinary personnel NR 158 NR NR 73 (46.2) NR NR
July 2013 Non-livestock workers NR 144 NR NR 94 (65.3) NR NR
October 2012–January 2014 Overall NR 677 NR NR 451 (66.6) NR NR
Finland/HIC Seuri and Koskela (1992) 1989 CS ELISA Livestock workers 20–65 53 41 12 20 (37.7) 15 (75) 5 (25)
Slaughterhouse workers 20–65 40 36 4 10 (25) 9 (90) 1 (10)
Overall 20–65 93 77 16 30 (32.3) 24 (80) 6 (20)
Northern Ireland/HIC Stanford et al. (1990) NR CS IHAT Livestock workers 18–83 407 NR NR 299 (73 5) NR NR
Slovak Republic/HIC Fecková et al. (2020) NR CS ELISA Livestock workers NR 219 NR NR 93 (42.5) NR NR
Veterinary personnel NR 294 NR NR 40 (13.6) NR NR
Non-livestock workers NR 196 NR NR 54 (27.6) NR NR
Overall NR 709 NR NR 187 (26.4) NR NR
Türkiye/UMIC Acici et al. (2008) NR CS ELISA Livestock workers NR 72 32 40 23 (31.9) 8 (34.8) 15 (65.2)
Poland/HIC Wójcik-Fatla et al. (2018) June–December 2017 CS ELFA Veterinary personnel 30–61 373 162 211 166 (44.5) 90 (54.2) 76 (45.8)
Portugal/HIC Almeida et al. (2022b) NR CC ELISA Veterinary personnel 19–63 350 98 252 91 (26) 25 (27.5) 66 (72.5)
  Portugal/HIC Almeida et al. (2022a) NR CS ELISA Livestock workers, slaughterhouse workers, and veterinary personnel 20–83 114 79 35 83 (72.8) 59 (71.1) 24 (28.9)
North America Canada/HIC Shuhaiber et al. (2003) 2002 CS ELISA Veterinary personnel 30–45 141 NR NR 20 (14.2) NR NR
Mexico/UMIC Alvarado-Esquivel et al. (2014) August 2013–July 2014 CC EIA Livestock workers 18–67 61 NR NR 2 (3.3) NR NR
Veterinary personnel 139 NR NR 10 (7.2) NR NR
Overall 200 NR NR 12 (6) NR NR
Mexico/UMIC Alvarado-Esquivel et al. (2011) September 2009–October 2010 CC EIA Slaughterhouse workers 16–71 124 103 21 7 (5.7) 6 (85.7) 1 (14.3)
Mexico/UMIC Galván-Ramírez et al. (2008) NR CS ELISA Slaughterhouse workers NR 145 NR NR 104 (71.7) NR NR
USA/HIC Rosypal et al. (2015) 2002–2006 CS ELISA Veterinary personnel NR 336 68 268 16 (4.8) 11 (68.7) 5 (31.3)
USA/HIC Weigel et al. (1999) 1993 CS MAT Livestock workers 18–83 174 NR NR 54 (31) NR NR
USA/HIC DiGiacomo et al. (1990) September 1979–March 1981 CS IFAT Veterinary personnel NR 61 NR NR 23 (37.7) NR NR
  USA/HIC Sengbusch and Sengbusch (1976) NR CC IFAT Veterinary personnel 15–66 60 NR NR 11 (18.3) NR NR
USA/HIC Riemann et al. (1974) NR CS IFAT Veterinary personnel NR 138 86 52 27 (19.6) 15 (55.6) 12 (44.4)
South America Brazil/UMIC Clazer et al. (2017) May–November 2014 CS IFAT Veterinary personnel NR 157 83 74 46 (29.3) 20 (43.5) 26 (56.5)
Brazil/UMIC Vicente et al. (2014) NR CC ELISA/IFAT Veterinary personnel NR 839 NR NR 183 (21.8) NR NR
Brazil/UMIC Gonçalves et al. (2006) July–September 2003 CS IFAT Slaughterhouse workers NR 150 113 37 105 (70) 80 (76.2) 25 (23.8)
Brazil/UMIC Dias et al. (2005) December 2002–January 2003 CS IFAT Slaughterhouse workers NR 47 43 4 28 (59.6) 25 (89.3) 3 (10.7)
Brazil/UMIC Riemann et al. (1975) January–July 1972 CS IFAT Slaughterhouse workers NR 144 124 20 103 (71.5) 86 (83.5) 17 (16.5)
Brazil/UMIC Riemann et al. (1974) NR CS IFAT Veterinary personnel NR 219 26 193 100 (45.7) 12 (12) 88 (88)
Chile/HIC Toro et al. (2017) NR CS CLIA Slaughterhouse workers, and veterinary personnel NR 39 NR NR 24 (61.5) NR NR
Colombia/UMIC Molina-Guzmán et al. (2019) NR CS ELISA Livestock workers 19–76 328 286 42 156 (47.6) 136 (87.2) 20 (12.8)
Trinidad and Tobago/HIC Adesiyun et al. (2011) NR CS EIA Livestock workers 18–60 394 313 81 150 (38.1) 119 (79.3) 31 (20.7)
Slaughterhouse workers 99 92 7 44 (44.4) 39 (88.6) 5 (11.4)
Overall 493 405 88 194 (39.4) 158 (81.4) 36 (18.6)
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Abbreviations: CC; Case-control study, CS; Cross-sectional study, CLIA; Chemiluminescence immunoassay, EIA; Enzyme immunoassay, ELISA; enzyme-linked immunosorbent assay, ELFA; Enzyme-linked fluorescence assays, HIC, high-income countries; ICT; Immuochromatography test, IFAT; Indirect fluorescent antibody technique, IHAT; modified agglutination test, LAT; latex agglutination test, LIC; low income countries, LMIC; low middle-income countries, NR; Not reported, MAT; modified agglutination test, RDT; Rapid diagnostic testing, UMIC; upper middle-income countries. Note: @Slaughterhouse workers from India were only involved in the slaughtering and selling of livestock (sheep and goat) and poultry meat; veterinary personnel (Professor/academicians, veterinary doctors, veterinary students working in clinics, veterinary pharmacists, veterinary technicians, and animal hospital workers).

Slaughterhouse workers were the most frequently studied population (n = 35, 53.0%), followed by veterinary personnel and livestock workers (n = 25 each, 37.9%). Only 9.1% of studies (n = 6) explored prevalence in non-livestock workers (animal attendants, handlers, hunters, fishermen, fish farm workers, and laboratory animal workers). Publication dates ranged from before 2000 (n = 13, 19.7%) to after 2010 (n = 37, 56.1%), with the most published between 2000 and 2010 (n = 17, 25.8%). All studies employed observational designs, with the vast majority being cross-sectional (n = 56, 84.8%) and a smaller number being case-control (n = 10, 15.2%).

A variety of diagnostic methods were used. Enzyme-linked immunosorbent assays (ELISA) were the most common (n = 32, 48.5%), followed by latex agglutination tests (LAT) (n = 12, 18.2%), indirect fluorescent antibody technique (IFAT) (n = 11, 16.7%), and enzyme immunoassay (EIA) (n = 4, 6.1%). Less frequent methods included enzyme-linked fluorescence assays (ELFA), indirect hemagglutination test (IHAT), modified agglutination test (MAT), chemiluminescence immunoassays (CLIA), immunochromatographic tests (ICT), rapid diagnostic testing (RDT), and polymerase chain reaction (PCR) (all n = 1, 1.5% each).

It is important to note that only 26 of the included studies (39.4%) reported data on the effect of gender on the prevalence of T. gondii infection.

3.3. Results of synthesis

This meta-analysis included data from 66 studies encompassing a total of 15,279 participants occupationally exposed to animals. The prevalence of T. gondii infection exhibited significant heterogeneity across the studies (p < 0.0001; I2 = 98.68%; τ2 = 0.05). This high level of heterogeneity indicates substantial variation in prevalence estimates between studies. Due to this heterogeneity, a random-effects model (REML) was employed for the final analysis. The pooled prevalence of T. gondii infection in workers occupationally exposed to animals across the globe was estimated to be 41% (95% CI: 36–47%) (Figure 2). This finding suggests a substantial burden of this parasitic infection among this occupational group. However, it is crucial to acknowledge the wide range of prevalence estimates reported in individual studies, ranging from a low of 4.8% (North America, USA, 2002–2006) to a high of 96.3% (Africa, Ghana, 2010s) (Table 4). This variation highlights the potential influence of factors such as geographic location, animal contact patterns, and diagnostic methods employed in the studies.

Figure 2.

Figure 2.

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Forest plot (random-effects model) of pooled T. gondii seroprevalence in WOEA worldwide.

Table 4.

Pooled prevalence estimates and heterogeneity measures of T. gondii infection in WOEA by subgroup characteristics.

Analysis of T. gondii infection Pooled estimates
 Heterogeneity
No of studies Pooled sample size Cases Pooled prevalence % (95% CI) Q-value tau2 I2% H2 Q-p value
Gender Male 26 2621 554 63 (54–72) 1486.96 0.051 97.5 40.07 <0.001
Female 26 2621 481 37 (28–46) 1486.96 0.051 97.5 40.07 <0.001
Study participants occupation Livestock workers 25 4776 2263 47 (38–55) 1693.45 0.042 97.71 43.67 <0.001
Non-livestock workers 6 600 307 54 (35–74) 381.64 0.059 97.4 38.52 <0.001
Slaughterhouse workers 35 4728 2187 44 (37–51) 2469.81 0.042 97.09 34.41 <0.001
Veterinary personnel 25 5126 1096 27 (19–34) 1620.38 0.036 99.23 129.7 <0.001
Continent Africa 17 3262 1944 51 (40–62) 963.85 0.049 98.04 51.13 <0.001
Asia 22 5122 1251 36 (26–45) 1100.96 0.048 98.65 74.23 <0.001
Australia 1 88 38 43 (33–54) 0.00 0.000 NE NE <0.001
Europe 9 3012 1428 47 (34–60) 555.02 0.038 98.25 57.05 <0.001
North America 9 1379 274 23 (9–37) 367.6 0.045 98.66 74.43 <0.001
South America 9 2416 939 49 (38–61) 322.55 0.030 97.08 34.28 <0.001
World Bank country income classification High-income 22 5743 2045 39 (30–48) 2225.28 0.046 98.73 78.99 <0.001
Upper-middle income 17 4425 1228 38 (28–49) 1042.54 0.049 98.76 80.56 <0.001
Lower-middle income 21 3744 1858 44 (33–54) 1987.17 0.061 98.36 61.06 <0.001
Low-income 7 1367 743 48 (32–64) 216.03 0.045 97.49 39.87 <0.001
Study year/s 1972–1981 4 561 241 39 (14–64) 128.31 0.062 97.74 44.25 <0.001
1982–1991 2 468 322 56 (21–91) 29.61 0.062 96.62 29.61 <0.001
1992–2001 7 854 348 43 (28–57) 136.61 0.035 95.21 20.89 <0.001
2002–2011 19 3391 985 39 (28–49) 1198.87 0.051 98.6 71.21 <0.001
2012–2023 35 10005 3978 42 (34–50) 4626.56 0.055v 98.93 93.28 <0.001
Overall 66 15279 5874 41 (36–47) 7357.52 0.05 98.68 75.52 <0.001
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3.4. Subgroup analysis

To address the substantial heterogeneity observed in the overall pooled prevalence estimate (I2 = 98.68%), a subgroup analysis was conducted to explore the potential influence of various factors on T. gondii infection rates among workers with occupational animal exposure (presented in Table 4).

3.4.1. Gender

The analysis revealed statistically significant differences in prevalence by gender (p < 0.05). Males exhibited a higher pooled prevalence (63%) compared to females (37%) (Figure 3). This translates to a prevalence ratio (PR) of approximately 1.7. In other words, males in this study were about 1.7 times more likely to have the condition than females.

Figure 3.

Figure 3.

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Forest plot (random-effects model) of pooled T. gondii seroprevalence in WOEA worldwide, stratified by gender.

3.4.2. Occupation

Occupation also emerged as a significant factor influencing prevalence (p < 0.05). Non-livestock workers displayed the highest prevalence (54%), followed by livestock workers (47%), slaughterhouse workers (44%), and veterinary personnel (27%)(Figure 4).

Figure 4.

Figure 4.

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The pooled seroprevalence of T. gondii infection in WOEA by continents.

3.4.3. Geographic region

A clear geographic trend was observed in the prevalence of T. gondii infection. Workers in Africa exhibited the highest prevalence (51%), followed by South America (49%), Europe (47%), Australia (43%), Asia (36%), and North America (23%).

3.4.4. World bank income classification

Interestingly, the analysis revealed a trend of lower prevalence in high-income (39%) and upper-­middle-income (38%) countries compared to lower-­middle-income (44%) and low-income (48%) countries. While statistically significant (p < 0.05), further investigation is warranted to elucidate the underlying mechanisms behind this association.

3.4.5. Study period

The subgroup analysis indicated a slight fluctuation in prevalence based on the study period, but no statistically significant temporal trend was evident (p > 0.05).

3.4.6. Diagnostic method

The prevalence of T. gondii infection was reported separately based on the type of laboratory test used. The studies employed both molecular tests (e.g. PCR) and serological tests (e.g. ELISA and IFAT). The pooled prevalence for studies using serological tests was 41% (95% CI: 36–47%), while the pooled prevalence for studies using molecular tests was 39% (95% CI: 28–49%).

Overall, this subgroup analysis provided valuable insights into potential sources of heterogeneity in the prevalence of T. gondii infection among workers with occupational animal exposure. These findings highlight the importance of considering gender, occupation, geographic location, and socioeconomic status when evaluating the risk of T. gondii infection in this population group.

3.5. Meta-regression, sensitivity analysis, and publication bias

To further explore the sources of heterogeneity in the overall prevalence estimate, a meta-regression analysis was conducted. This analysis investigated the potential association between various study characteristics and the prevalence of T. gondii infection (Figure 5). All examined variables, except study design, displayed a statistically significant association with prevalence in the univariate meta-regression analysis. However, when a multivariate meta-regression model was employed, only the country of the study participants remained statistically significant (Table 5). This suggests that country-specific factors likely account for a substantial portion of the observed heterogeneity between studies.

Figure 5.

Figure 5.

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Meta-regression analysis: scatter plot depicting the relationship between study variables and pooled T. gondii seroprevalence estimates in WOEA.

Table 5.

Random-effects meta-regression analysis of factors associated with T. gondii seroprevalence in WOEA.

Univariate regression
Variables Coefficient SE Z p Value 95%CI I2 R2
Study participants occupation 0.566 0.057 9.96 <0.001 (0.454–0.677) 98.71 9.87%
Continent 0.448 0.054 8.30 <0.001 (0.342–0.554) 98.65 0.001%
Country 0.481 0.054 8.86 <0.001 (0.375 − 0.588) 98.59 1.78%
Income classification 0.41 0.065 6.29 <0.001 (0.282–0.537) 98.63 0.001%
Study period 0.433 0.063 6.9 <0.001 (0.31–0.556) 98.62 0.001%
Study design 0.091 0.142 0.64 0.523 (-0.188–0.369) 98.56 6.29%
Diagnostic method 0.389 0.076 5.12 <0.001 (0.24–0.537) 98.66 0.001%
Sample size 0.419 0.041 10.35 <0.001 (0.34–0.498) 98.67 0.001%
Multivariate regression
Variables Coefficient SE Z p Value 95%CI    
Intercept 0.63 0.165 3.82 <0.001 (0.307–0.954) 98.46 0.001%
Continent −0.017 0.018 −0.96 0.338 (-0.052–0.0177)
Country −0.006 0.003 −2.00 0.045 (-0.013–0.0001)
Income classification −0.031 0.028 −1.10 0.273 (-0.086–0.024)
Study period −0.005 0.037 −0.12 0.902 (-0.077–0.068)
Diagnostic method 0.007 0.015 0.51 0.611 (-0.022–0.037)
Sample size −0.001 0.002 −0.17 0.864 (-0.005–0.004)
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A sensitivity analysis was performed to assess the robustness of the meta-analysis findings. This analysis involved sequentially excluding studies from the model and evaluating any resulting changes in the pooled prevalence estimate. No significant differences in the pooled prevalence were observed, indicating that the overall findings were relatively stable and not unduly influenced by any single study (see details).

Finally, potential publication bias was evaluated using two methods: a funnel plot (Figure 6) and Egger’s regression test. The funnel plot displayed a symmetrical appearance, and Egger’s test did not yield a statistically significant result (p = 0.176). These findings suggest a low likelihood of publication bias significantly influencing the meta-analysis results.

Figure 6.

Figure 6.

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Funnel plot for evaluation of publication bias in the meta-analysis of pooled T. gondii seroprevalence in WOEA worldwide.

4. Discussion

This systematic review and meta-analysis underscore the significant public health burden of T. gondii infection among workers with occupational animal exposure (WOEA) on a global scale. The high pooled prevalence of 41% (95% CI: 36–47%), derived from 66 studies encompassing over 15,000 participants, translates to a significant proportion of WOEA workers testing positive for antibodies against T. gondii, indicating a past or current infection.

The significance of this elevated prevalence lies in the clear distinction between WOEA workers and the general population. While existing research suggests that around 30% of the general population carries T. gondii antibodies (Rahmanian et al. 2020), our analysis demonstrates a demonstrably higher rate of infection, specifically within the WOEA group.

This disparity underscores the heightened risk faced by WOEA workers due to their occupational exposure to animals. The nature of their jobs likely increases their chances of encountering T. gondii, a parasite commonly found in animals like cats and some livestock.

The observed heterogeneity in prevalence across studies (I2 = 98.68%) suggests the influence of various factors. Notably, our analysis revealed a significant geographic disparity in seroprevalence, with the highest burden observed in African WOEA (51%). This finding aligns with previous research on zoonotic diseases like Brucella and tuberculosis in WOEA, highlighting the increased risk of occupational zoonoses in Africa compared to other regions (Mia et al. 2022).

Several factors are likely to contribute to this geographic disparity. Hot and humid climates prevalent in many African regions favor the sporulation and environmental persistence of T. gondii oocysts (Afonso et al. 2013; Yan et al. 2016). This extended environmental survival period translates to a heightened exposure risk for WOEA engaged in outdoor work and having frequent contact with soil or potentially contaminated areas.

Furthermore, animal husbandry practices in Africa, such as free-roaming livestock, can contribute to widespread oocyst contamination of pastures and grazing areas, thereby increasing exposure risk for WOEA herding or tending to these animals (Seo and Mendelsohn 2008). Limited access to veterinary care and preventive measures for animal diseases in some African countries further exacerbates the situation. This, coupled with the potential impact of wars and armed conflicts on the continent (Mohammed and Ahmed 2023), might contribute to a higher prevalence of T. gondii in animal populations, ultimately increasing the risk of transmission to WOEA.

Lower socioeconomic development in some African countries can also play a role. Poorer sanitation practices and limited access to clean water can increase environmental exposure to oocysts for both WOEA and the general population. Additionally, cultural practices involving the consumption of raw or undercooked meat, more common in some parts of Africa (Abdelnabi et al. 2016), pose a higher risk for WOEA who handle or slaughter animals.

The observed geographic disparity suggests a potential research gap in T. gondii infection among WOEA in certain African regions compared to developed countries.

This gap could lead to an underestimation of the true prevalence and hinder the development of targeted preventive measures. To address this disparity and protect at-risk populations, we propose increased awareness campaigns among WOEA and healthcare professionals regarding T. gondii infection and its transmission routes. Improved knowledge can empower WOEA to adopt preventive behaviors and facilitate early diagnosis.

The trend of lower seroprevalence in high-income countries suggests a potential influence of socioeconomic factors on T. gondii exposure among WOEA. Improved sanitation practices, access to clean water, and better veterinary care for animals, all more prevalent in developed nations, can significantly reduce environmental oocyst contamination.

The current analysis revealed an intriguing trend within the WOEA population. Non-livestock workers exhibited the highest pooled prevalence of T. gondii infection (54%), followed by livestock workers and slaughterhouse workers. Interestingly, veterinary personnel displayed the lowest prevalence (27%). Several potential explanations warrant further investigation.

One possibility relates to exposure dynamics. The broad category of ‘non-livestock workers’ likely encompasses a diverse range of professions with varying degrees and types of animal contact. This includes zookeepers, wildlife rehabilitators, shearers, fishermen, fish farm workers, animal hunters, or personnel in pet stores and grooming facilities. These jobs might involve exposure to a wider variety of animal species compared to those working primarily with livestock. A broader host range of exposure could increase the chance of encountering infected animals, potentially explaining the higher prevalence observed in non-livestock workers.

Conversely, livestock and slaughterhouse workers, while still at risk, might develop a degree of immunological tolerance through repeated low-dose exposures to T. gondii within specific livestock populations (e.g. cattle, pigs, and sheep) (Sana et al. 2022).

Another potential explanation is the influence of hygiene practices and biosecurity protocols. Veterinary personnel are likely to be more cognizant of the risks associated with T. gondii and implement stricter hygiene protocols in their work environment. This could encompass consistent use of personal protective equipment (PPE) like gloves and masks, adherence to meticulous handwashing procedures, and maintaining a sanitized workspace (Odo et al. 2015; Habib and Alshehhi 2021; Kimindu et al. 2024). These practices can significantly mitigate the risk of oocyst ingestion.

In contrast, adherence to hygiene protocols might be less consistent among non-livestock workers and some livestock workers, depending on the specific job role and workplace culture. Jobs with a higher risk of exposure, such as shearing or handling birthing animals, might necessitate more stringent hygiene practices compared to roles with less frequent direct animal contact. Additionally, the availability and accessibility of PPE and handwashing facilities within the workplace can influence adherence to hygiene protocols.

Further research is needed to elucidate the specific reasons behind these observed variations. Investigating the specific work activities and animal contact patterns within each WOEA category could provide valuable insights into exposure dynamics. Additionally, exploring the level of training and awareness about T. gondii infection and preventive measures across different professions could shed light on potential discrepancies in hygiene practices and risk perception. By examining these factors in a comprehensive manner, researchers and public health professionals can develop more targeted interventions to effectively reduce the risk of T. gondii infection for all WOEA populations.

Our subgroup analysis revealed a statistically significant difference in T. gondii infection prevalence by gender (p < 0.05), with males exhibiting a higher pooled prevalence compared to females. This disparity may be attributable to a confluence of factors, including potential behavioral and occupational variations. Certain occupations within the WOEA category might be more male-dominated and involve activities associated with a higher risk of T. gondii exposure. Examples include jobs in shearing, herding, or cull animal disposal, which often fall under the non-livestock worker category. These roles may involve more frequent and direct contact with bodily fluids or contaminated environments compared to positions typically filled by females (Habib et al. 2014). Additionally, gender-based differences in risk perception and adherence to hygiene protocols could contribute to the observed disparity. Males might be less likely to perceive the importance of meticulous handwashing or the consistent use of personal protective equipment (PPE), potentially increasing their risk of accidental oocyst ingestion.

This review’s findings yielded significant insights for policymakers and healthcare professionals regarding the historical burden of T. gondii infection within the WOEA group. This information informed the development and implementation of interventions to mitigate infection risk and enhance toxoplasmosis management in this population group.

Policymakers may leverage the review’s findings to formulate evidence-based policies aimed at curtailing T. gondii infection risk within the WOEA population group. This could entail the development of regulations mandating employers furnish workers with suitable PPE and training. Additionally, the establishment of funding programs to support employers in implementing these measures might be undertaken.

Healthcare professionals may utilize the review’s insights to refine the management of toxoplasmosis within the WOEA population. This could involve the development of screening programs to identify infected workers and provide them with appropriate treatment and counseling. Furthermore, the creation of educational materials to educate workers on T. gondii infection risks and preventative measures might have been implemented.

Public health authorities may develop targeted educational campaigns during the relevant timeframe to raise awareness concerning T. gondii infection risks and the significance of preventative measures. Studying the historical prevalence of T. gondii infection within the WOEA population served the dual purpose of safeguarding worker health and promoting broader public health initiatives, as T. gondii possesses the capacity for transmission from pregnant women to their fetuses and through foodborne illness. By comprehending the historical prevalence of infection among workers handling food animals, public health officials are better equipped to identify and mitigate potential public health risks.

The current study acknowledges limitations inherent to meta-analysis methodology. The use of varying diagnostic methods across studies is recognized as a limitation. Additionally, data on specific work practices and hygiene behaviors was limited in the included studies. This limited data availability restricts the ability to definitively assess their impact on infection risk.

5. Conclusion

This systematic review and meta-analysis estimated a high global seroprevalence (41%, 95% CI: 36–47%) of T. gondii infection among workers occupationally exposed to animals. Substantial heterogeneity was observed, with subgroup analyses revealing significant variations by gender, occupation, geographic region, and income classification. Country-specific factors likely contributed most to this heterogeneity. These findings highlight the need for targeted interventions to reduce the risk of T. gondii infection in this high-risk population, considering factors such as occupation and geographic location. Further research is warranted to elucidate the mechanisms underlying the observed disparities and to develop effective preventive strategies.

Funding Statement

The author(s) reported there is no funding associated with the work featured in this article.

Authors’ contributions

Abdullah Mohammed: conceptualization, methodology (search strategy), data curation, formal analysis, investigation, writing (original draft & revisions). Musa Ahmed: methodology (search strategy), data curation, investigation, review & editing. Nasir Ibrahim: methodology (search strategy), data curation, investigation, review & editing. All authors: approved the final manuscript.

Disclosure statement

No potential conflict of interest was reported by the author(s).

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