Prevalence and distribution of soil-borne zoonotic pathogens in Lahore district of Pakistan

Epidemiology of tularemia in the countries of the WHO Eastern Mediterranean Region (EMRO): A systematic review and meta-analysis

BACKGROUND

Francisella tularensis, the bacterium that causes tularemia, has been a persistent and widespread pathogen in various regions of the world for centuries. Francisella tularensis can affect humans and various domestic and wild animals. The current study aimed to determine the epidemiological status of tularemia in countries of the WHO Eastern Mediterranean Region (EMRO) through a systematic review and meta-analysis.

METHODS

All included studies were identified through a systematic search of online databases, including Scopus, PubMed, Web of Science, and EMBASE, through July 26, 2022, using keywords and suitable combinations. We focused on cross-sectional studies investigating the prevalence of F. tularensis. The weighted pooled prevalence was calculated using a random-effects model.

RESULTS

A total of 206 studies were identified, of which 20 were finally included in the analysis. The human seroprevalence of tularemia in WHO-EMRO countries was 6.2% (95% CI, 4.2 9.2). In the subgroup analysis, anti-F. tularensis antibodies were found in 6.92% and 5.5% of the high-risk individuals and Iran, respectively. The pooled prevalence of F. tularensis in environmental samples (water and soil) from the WHO-EMRO countries was 5.8% (9.4% by PCR and 0.5% by culture). In addition, 2.5% (95% CI, 0.2 0.22.7) of ticks in WHO-EMRO countries were positive for F. tularensis. The pooled prevalence of F. tularensis in rodents is 2.0% (1.1% by PCR and 3.7% by serology). In addition, 0.6% of domestic ruminants (0.4% by PCR and 2.4% by serology) were positive for F. tularensis in WHO-EMRO countries.

CONCLUSION

According to the results of the present study, tularemia is an endemic but neglected disease in the WHO-EMRO region. However, most studies on tularemia are limited to a few countries in this region. Studies on tularemia in human populations, reservoirs, and vectors have been conducted in all countries in the WHO-EMRO region to obtain more detailed information about the epidemiology of tularemia in these regions.

Molecular detection of Coxiella burnetii in ticks collected from Iran

The present study was conducted with the aim of investigating the prevalence and genetic structure of Coxiella burnetii in tick samples collected from domestic animals in Hormozgan province146 tick samples were randomly collected from cattle, sheep, goat, camel and dog herds in seven cities of Hormozgan. After the DNA was extracted from each tick sample; Nested-PCR method was used to identify the presence of C. burnetii using IS1111 transposon gene and isocitrate dehydrogenase icd gene. In addition, phylogenetic analysis and tree diagram were constructed based on IS1111 and icd genes. The results showed that out of 146 pool tick samples, 40 pool samples based on IS1111 gene and 32 pool samples based on icd gene were infected with C. burnetii. When results were stratified by livestock type, infection rates were highest in sheep ticks (37.5%, 95% CI: 21.2% - 57.29%), followed by cattle ticks (32.14%, 95% CI: 17.90% - 50.66%) and dog tick (15%, 95% CI: 70.6% - 29%). In camel and goat ticks, the infection rate was 15.90 and 23.07%, respectively. In conclusion, this study emphasizes the role of ticks as potential carriers of C. burneti. The results indicate the importance of cattle, sheep, goats, camels and dogs in Hormozgan region as effective factors in the epidemiology of Q fever and its impact on public health. In addition, a high degree of similarity (from 99% to 100%) was observed between IS1111 and icd genes in this study and recorded sequences from different regions of the world.

Identifying key soil characteristics for Francisella tularensis classification with optimized Machine learning models

Francisella tularensis (Ft) poses a significant threat to both animal and human populations, given its potential as a bioweapon. Current research on the classification of this pathogen and its relationship with soil physical-chemical characteristics often relies on traditional statistical methods. In this study, we leverage advanced machine learning models to enhance the prediction of epidemiological models for soil-based microbes. Our model employs a two-stage feature ranking process to identify crucial soil attributes and hyperparameter optimization for accurate pathogen classification using a unique soil attribute dataset. Optimization involves various classification algorithms, including Support Vector Machines (SVM), Ensemble Models (EM), and Neural Networks (NN), utilizing Bayesian and Random search techniques. Results indicate the significance of soil features such as clay, nitrogen, soluble salts, silt, organic matter, and zinc , while identifying the least significant ones as potassium, calcium, copper, sodium, iron, and phosphorus. Bayesian optimization yields the best results, achieving an accuracy of 86.5% for SVM, 81.8% for EM, and 83.8% for NN. Notably, SVM emerges as the top-performing classifier, with an accuracy of 86.5% for both Bayesian and Random Search optimizations. The insights gained from employing machine learning techniques enhance our understanding of the environmental factors influencing Ft's persistence in soil. This, in turn, reduces the risk of false classifications, contributing to better pandemic control and mitigating socio-economic impacts on communities.

Molecular detection of Coxiella spp. in ticks (Ixodidae and Argasidae) infesting domestic and wild animals: with notes on the epidemiology of tick-borne Coxiella burnetii in Asia

Tick-borne Coxiella spp. are emerging in novel regions infecting different hosts, but information regarding their occurrence is limited. The purpose of this study was the molecular screening of Coxiella spp. in various ticks infesting goats, sheep, camels, cattle, wild mice, and domestic fowls (Gallus gallus domesticus) in various districts of Khyber Pakhtunkhwa, Pakistan. Morphologically identified tick species were confirmed by obtaining their cox1 sequences and were molecularly screened for Coxiella spp. by sequencing GroEL fragments. Almost 345 out of 678 (50.9%) hosts were infested by nine tick species. Regarding the age groups, the hosts having an age >3 years were highly infested (192/345, 55.6%), while gender-wise infestation was higher in female hosts (237/345, 68.7%). In collected ticks, the nymphs were outnumbered (613/1,119, 54.8%), followed by adult females (293/1,119, 26.2%) and males (213/1,119, 19.7%). A total of 227 ticks were processed for molecular identification and detection of Coxiella spp. The obtained cox1 sequences of nine tick species such as Hyalomma dromedarii, Hyalomma anatolicum, Haemaphysalis cornupunctata, Haemaphysalis bispinosa, Haemaphysalis danieli, Haemaphysalis montgomeryi, Rhipicephalus haemaphysaloides, Rhipicephalus microplus, and Argas persicus showed maximum identities between 99.6% and 100% with the same species and in the phylogenetic tree, clustered to the corresponding species. All the tick species except Ha. danieli and R. microplus were found positive for Coxiella spp. (40/227, 17.6%), including Coxiella burnetii (15/40, 6.7%), Coxiella endosymbionts (14/40, 6.3%), and different Coxiella spp. (11/40, 4.9%). By the BLAST results, the GroEL fragments of Coxiella spp. showed maximum identity to C. burnetii, Coxiella endosymbionts, and Coxiella sp., and phylogenetically clustered to the corresponding species. This is the first comprehensive report regarding the genetic characterization of Coxiella spp. in Pakistan's ticks infesting domestic and wild hosts. Proper surveillance and management measures should be undertaken to avoid health risks.

Two phase feature-ranking for new soil dataset for Coxiella burnetii persistence and classification using machine learning models

Coxiella burnetii (Cb) is a hardy, stealth bacterial pathogen lethal for humans and animals. Its tremendous resistance to the environment, ease of propagation, and incredibly low infectious dosage make it an attractive organism for biowarfare. Current research on the classification of Coxiella and features influencing its presence in the soil is generally confined to statistical techniques. Machine learning other than traditional approaches can help us better predict epidemiological modeling for this soil-based pathogen of public significance. We developed a two-phase feature-ranking technique for the pathogen on a new soil feature dataset. The feature ranking applies methods such as ReliefF (RLF), OneR (ONR), and correlation (CR) for the first phase and a combination of techniques utilizing weighted scores to determine the final soil attribute ranks in the second phase. Different classification methods such as Support Vector Machine (SVM), Linear Discriminant Analysis (LDA), Logistic Regression (LR), and Multi-Layer Perceptron (MLP) have been utilized for the classification of soil attribute dataset for Coxiella positive and negative soils. The feature-ranking methods established that potassium, chromium, cadmium, nitrogen, organic matter, and soluble salts are the most significant attributes. At the same time, manganese, clay, phosphorous, copper, and lead are the least contributing soil features for the prevalence of the bacteria. However, potassium is the most influential feature, and manganese is the least significant soil feature. The attribute ranking using RLF generates the most promising results among the ranking methods by generating an accuracy of 80.85% for MLP, 79.79% for LR, and 79.8% for LDA. Overall, SVM and MLP are the best-performing classifiers, where SVM yields an accuracy of 82.98% and 81.91% for attribute ranking by CR and RLF; and MLP generates an accuracy of 76.60% for ONR. Thus, machine models can help us better understand the environment, assisting in the prevalence of bacteria and decreasing the chances of false classification. Subsequently, this can assist in controlling epidemics and alleviating the devastating effect on the socio-economics of society.

Sero-Epidemiology of Coxiella burnetii Infection in Small Ruminants in the Eastern Region of Punjab, Pakistan

The aim of this study was to investigate the seroprevalence of Q fever in sheep and goats in Kasur, Okara, and Pakpattan in the Punjab of Pakistan. Q fever is a widely reported zoonotic disease caused by Coxiella (C.) burnetii. The main reservoirs are small ruminants that excrete the bacteria in birth by-products in high numbers. Thus, the bacteria can also be detected in the air and the dust of livestock farms. The infection is often asymptomatic in ruminants, but it can lead to reproductive disorders. This cross-sectional study found that a significant number (n = 43; 11.3%) of 300 randomly selected small ruminants of nine tehsils were seropositive using a commercially available ELISA. Seroprevalence was significantly higher in goats (17.1%) than in sheep (4.9%). Binary logistic regression analysis proved that species, age, and breed have a significant effect on the prevalence of Q fever. Tick infestation, contact with animal fomites, contact with other animals, production system, and health status of an animal had a significant impact on the prevalence of Q fever. These findings on Q fever in animals can be used to improve the visibility of this zoonotic disease. These findings will help local health authorities to focus on the origin of the problem and facilitate applying preventive measures to the affected livestock farms.

One Health Paradigm to Confront Zoonotic Health Threats: A Pakistan Prospective

The emergence and re-emergence of zoonotic diseases significantly impact human health, particularly those who live in impoverished areas and have close contact with domestic or wild animals. Nearly 75% of zoonotic diseases are transmitted directly from animals to humans or indirectly via vector/agent interactions between animals and humans. Growing populations, globalization, urbanization, and the interaction of the environment with humans and livestock all play roles in the emergence and spread of zoonotic diseases. "One Health" is a multidisciplinary concept aimed at improving human, animal, and environmental health, but this concept is not widely accepted in developing countries. In Pakistan, environmental, human, and animal health are severely affected due to a lack of sufficient resources. This review article provides an overview of the most common zoonotic diseases found in Pakistan and emphasizes the importance of the "One Health" concept in managing these diseases. Given the current situation, interdisciplinary research efforts are required to implement and sustain effective and long-term control measures in animal, human, and environmental health surveillance and accurate diagnostic methods.

Current perspectives on the occurrence of Q fever: highlighting the need for systematic surveillance for a neglected zoonotic disease in Indian subcontinent

Coxiellosis or Q fever is an important global occupational zoonotic disease caused by one of the most contagious bacterial pathogens - Coxiella burnetii, which ranks one among the 13 global priority zoonoses. The detection of C. burnetii infection is exhibiting an increasing trend in high-risk personnel around the globe. It has increasingly been detected from foods of animal origin (including bulk milk, eggs, and meat) as well as tick vectors in many parts of the world. Coxiellosis is reported to be an important public health threat causing spontaneous abortions in humans and potential reproductive failure, which would result in production losses among livestock. Further, comprehensive coverage of the reports and trends of Q fever in developing countries, where this infection is supposed to be widely prevalent appears scarce. Also, the pathogen remains grossly neglected and underreported. Moreover, policymakers and funding agencies do not view it as a priority problem, especially in the Indian subcontinent, including Sri Lanka, Bhutan, Pakistan, Nepal, Bangladesh and Maldives. Here, we review the occurrence and epidemiology of the disease in a global context with special emphasis on its status in the Indian subcontinent.

Identification of Most Relevant Features for Classification of Francisella tularensis using Machine Learning

Background:

Francisella tularensis is a stealth pathogen fatal for animals and humans. Ease of its propagation, coupled with high capacity for ailment and death makes it a potential candidate for biological weapon.

Objective:

Work related to the pathogen’s classification and factors affecting its prolonged existence in soil is limited to statistical measures. Machine learning other than conventional analysis methods may be applied to better predict epidemiological modeling for this soil-borne pathogen.

Methods:

Feature-ranking algorithms namely; relief, correlation and oneR are used for soil attribute ranking. Moreover, classification algorithms; SVM, random forest, naive bayes, logistic regression and MLP are used for classification of the soil attribute dataset for Francisella tularensis positive and negative soils.

Results:

Feature-ranking methods concluded that clay, nitrogen, organic matter, soluble salts, zinc, silt and nickel are the most significant attributes while potassium, phosphorous, iron, calcium, copper, chromium and sand are the least contributing risk factors for the persistence of the pathogen. However, clay is the most significant and potassium is the least contributing attribute. Data analysis suggests that feature-ranking using relief produced classification accuracy of 84.35% for multilayer perceptron; 82.99% for linear regression; 80.27% for SVM and random forest; and 78.23% for naive bayes, which is better than other ranking methods. MLP outperforms other classifiers by generating an accuracy of 84.35%, 82.99% and 81.63% for feature-ranking using relief, correlation and oneR algorithms, respectively.

Conclusion:

These models can significantly improve accuracy and can minimize the risk of incorrect classification. They further help in controlling epidemics and thereby minimizing the socio-economic impact on the society.

Coxiella burnetii in the environment: A systematic review and critical appraisal of sampling methods

Q fever is a zoonotic disease caused by the intracellular bacterium, Coxiella burnetii. Its primary mode of transmission is by inhalation of aerosols originating from infected animals and contaminated environments. The organism has a very low infective dose, can persist in the environment for long periods of time and large outbreaks fuelled by windborne spread have been previously reported. Detection of C. burnetii in the environment is therefore important during human and animal outbreak investigations and for the control and prevention of Q fever. This study aimed to systematically review and critically appraise the published literature on sampling methods used to detect C. burnetii from different environmental samples. A search of four electronic databases with subsequent hand searching identified 47 eligible articles published since 1935. These articles described sampling of dust, air, soil and liquids in attempts to detect C. burnetii during 19 Q fever outbreaks and in 28 endemic settings. Environmental positivity was most commonly associated with ruminant livestock populations. Evidence describing spatio-temporal characteristics and associated geographical dispersion gradients was limited. The most commonly tested sample type was dust which also yielded the highest bacterial loads of >10⁸ bacteria/cloth. The MD8 (Sartorius) air sampler was used widely for air sampling. Soil was the only sample type for which a validated laboratory protocol was established specifically for C. burnetii. Each environmental sample type has its advantages and limitations which are discussed in detail and a simplified framework to guide decisions around environmental sampling for C. burnetii is provided. In any type of environmental sampling, it is recommended to use standardized and validated methods and to match the most ideal sampling strategy and timing with the research context. These conditions are essential to be considered when designing future Q fever management plans that involve environmental sampling for C. burnetii.

Surveillance of Francisella tularensis in surface water of Kurdistan province, west of Iran

BACKGROUND

The etiologic agent of tularemia, Francisella tularensis, is transmitted to humans via ingestion of contaminated water or food, arthropods bite, respiratory aerosols, or direct contact with infected animals body fluids or tissues. In the current study, due to the importance of water in transmitting the disease and the report of the disease in different regions of Iran, surface water of Kurdistan province were evaluated for the presence of F.tularensis.

MATERIALS AND METHODS

Sampling was carried out in five-counties of Kurdistan province. Sixty-six specimens of surface water were collected. The detection was carried out by targeting ISFtu2 and fopA genes using TaqMan real-time PCR. Moreover, the samples were both cultured and inoculated into NMRI inbreed mice. Spleens of inoculated mice and bacterial isolates were tested by TaqMan real-time PCR.

RESULTS

Despite the lack of isolation of F. tularensis, the results of the molecular testing indicate the presence of bacteria in surface water. Molecular positivity of one sample (1.51%) was confirmed using a real-time PCR for both ISFtu2 and fopA genes. Moreover, 4.54% of the samples were positive for ISFtu2.

CONCLUSION

Since the in vitro isolation of bacteria from environmental samples is associated with a very low success rate and depends on various environmental parameters, the use of molecular techniques for monitoring of the bacteria in the contaminated areas is fully recommended.

The prevalence of Francisella spp. in different natural surface water samples collected from northwest of Iran

BACKGROUND AND OBJECTIVES

Francisella tularensis has a wide distribution in northern hemisphere of the world. Up to now, there was little information about the Francisella spp. situation in the environmental samples in Iran. In this study we aimed to determine the prevalence of Francisella spp. in the environmental samples in northwest of Iran.

MATERIALS AND METHODS

A total of 237 natural water samples from ponds, rivers, lakes, springs and other surface waters from north western provinces of Iran (Kurdistan and Western Azerbaijan) were collected from September to November 2015. All samples were cultured for Francisella and other bacterial species and Real Time TaqMan PCR was performed on the concentrated and DNA extracted samples. For detection of the presence of bacterial DNA in the samples, two different targets in the genome of Francisella, ISFtu2 and fopA were used.

RESULTS

Among the tested surface water samples, 40 (17.09%; 95% CI: 12.67-22.33%) and 12 (5.13%; 95%CI: 2.81-8.56%) samples were positive for ISFtu2 and fopA respectively. None of them was positive in culture.

CONCLUSION

The prevalence of Francisella spp. in the environmental samples in the west of Iran is high and it is comparable with Turkey, Iran's neighboring country. Use of higher copy number genes or IS like ISFtu2 could improve the detection of this organism in the environmental samples.

Melioidosis in South Asia (India, Nepal, Pakistan, Bhutan and Afghanistan)

Despite the fact that South Asia is predicted to have the highest number of cases worldwide, melioidosis is a little-known entity in South Asian countries. It has never been heard of by the majority of doctors and has as yet failed to gain the attention of national Ministries of Health and country offices of the World Health Organization (WHO). Although a few centers are diagnosing increasing numbers of cases, and the mortality documented from these institutions is relatively high (nearly 20%), the true burden of the disease remains unknown. In India, most cases have been reported from southwestern coastal Karnataka and northeastern Tamil Nadu, although this probably simply reflects the presence of centers of excellence and researchers with an interest in the disease. As elsewhere, the majority of cases have type 2 diabetes mellitus and occupational exposure to the environment. Most present with community-acquired pneumonia and/or bacteremia, especially during heavy rainfall. The high seropositivity rate (29%) in Karnataka and isolation of B. pseudomallei from the environment in Tamil Nadu and Kerala confirm India as melioidosis-endemic, although the full extent of the distribution of the organism across the country is unknown. There are limited molecular epidemiological data, but, thus far, the majority of Indian isolates have appeared distinct from those from South East Asia and Australia. Among other South Asian countries, Sri Lanka and Bangladesh are known to be melioidosis-endemic, but there are no cases that have conclusively proved to have been acquired in Nepal, Bhutan, Afghanistan or Pakistan. There are no surveillance systems in place for melioidosis in South Asian countries. However, over the past two years, researchers at the Center for Emerging and Tropical Diseases of Kasturba Medical College, University of Manipal, have established the Indian Melioidosis Research Forum (IMRF), held the first South Asian Melioidosis Congress, and have been working to connect researchers, microbiologists and physicians in India and elsewhere in South Asia to raise awareness through training initiatives, the media, workshops, and conferences, with the hope that more patients with melioidosis will be diagnosed and treated appropriately. However, much more work needs to be done before we will know the true burden and distribution of melioidosis across South Asia.

Subterranean Mammals: Reservoirs of Infection or Overlooked Sentinels of Anthropogenic Environmental Soiling?

Global reports of emergent pathogens in humans have intensified efforts to identify wildlife reservoirs. Subterranean mammals, such as bathyergid mole rats, are largely overlooked, despite their high-level exposure to soil-dwelling microbes. Initial assessment of bathyergid reservoir potential was determined using a broad-range 16S rRNA PCR approach, which revealed an 83% PCR-positivity for the 234 bathyergid lung samples evaluated. The presence of the Bacillus cereus complex, a ubiquitous bacterial assemblage, containing pathogenic and zoonotic species, was confirmed through nucleotide sequencing, prior to group- and species-specific PCR sequencing. The latter allowed for enhanced placement and prevalence estimations of Bacillus in four bathyergid species sampled across a range of transformed landscapes in the Western Cape Province, South Africa. Two novel Bacillus strains (1 and 2) identified on the basis of the concatenated 16S rRNA-groEL-yeaC data set (2066 nucleotides in length), clustered with B. mycoides (ATCC 6462) and B. weihenstephanensis (WSBC 10204), within a well-supported monophyletic lineage. The levels of co-infection, evaluated with a groEL strain-specific assay, developed specifically for this purpose, were high (71%). The overall Bacillus presence of 17.95% (ranging from 0% for Georychus capensis to 45.35% for Bathyergus suillus) differed significantly between host species (χ² = 69.643; df = 3; P < 0.05), being significantly higher in bathyergids sampled near an urban informal settlement (χ² = 70.245; df = 3; P < 0.05). The results highlight the sentinel potential of soil-dwelling mammals for monitoring anthropogenically introduced, opportunistic pathogens and the threats they pose to vulnerable communities, particularly in the developing world.

Seroprevalence and risk factors of glanders in working equines - Findings of a cross-sectional study in Punjab province of Pakistan

Glanders is an infectious and contagious bacterial disease of equines. A little is known about its seroprevalence and risk factors in working equines in countries where the disease is endemic. Also, there are no reports on prevalence of the disease in areas where there is a prior evidence of Burkholderia (B.) mallei detection in soil. A cross-sectional study was conducted in selected districts (n=09) of Punjab province of Pakistan during 2014-2015. A total of 1008 serum samples were screened for detection of antibodies to B. mallei with complement fixation test followed by western blot. The overall seroprevalence was found to be 3.17% (95% CI: 2.25-4.44). The seropositivity was significantly higher from the sampling sites where B. mallei was detected in soil [OR: 10.66 (95% CI: 4.42-31.66), p=0.00]. Other risk factors significantly associated with animal seropositivity were: age group [OR: 1.78 (95% CI: 4.58-15.56), p=0.00], location in urban area [OR: 2.99 (95% CI: 1.46-6.51), p=0.00],body condition [OR: 3.47 (95% CI: 1.64-7.99), p=0.00], presence of farcy lesion[OR: 7.71 (95% CI: 3.47-19.50), p=0.00], proximity to water bodies [OR: 7.71 (95% CI: 3.47-19.50), p=0.00]; domestic animal population [OR: 3.20 (95% CI: 1.24-10.87), p=0.03] and number of households in sampling area [OR: 4.18 (95%CI: 1.82-11.30), p=0.00]. The study provides an estimate of prevalence of glanders and a potential link between animal seropositivity and presence of B. mallei in soil. The risk factors identified in this study can be used in surveillance and disease awareness. The high prevalence of disease in draught horses and contact of infected animals with their care-takers in developing countries signify need to initiate progressive control of the disease using one health approach.

Evidence of Coxiella burnetii in Punjab province, Pakistan

Coxiella burnetii causes query (Q) fever, an important zoonotic disease with worldwide significance. The role of environment in the ecology of C. burnetti, and its influence on seroconversion in animals has not been elucidated in Pakistan. We carried out a cross-sectional study in Punjab province to (1) determine the prevalence and distribution of C. burnetii in soil using an ISIIII gene-based real time-polymerase chain reaction (RT-PCR) assay, (2) analyze association between the occurrence of C. burnetii in soil and its predictors i.e. soil characteristics (macro- and micro-nutrients) and several likely risk factors including the seroconversion in small ruminants at places where its genome had or had not been detected, and (3) predict homology and genetic diversity of the identified strains using sequences originated from different hosts worldwide. A total of 2425 soil samples from nine districts of Punjab province were processed. C. burnetii DNA was detected in 47 samples (1.94%, 95% CI: ±0.55) originating from 35 villages of studied districts (7.22%, 95% CI: ±2.30). The highest prevalence was found in Attock (7.11%, 95% CI: ±3.36), followed by Lahore (4.83%, 95% CI: ±3.49), Sahiwal (4.70%, 95% CI: ±2.6), Dera Ghazi Khan (2.33%, 95% CI: ±2.02), Faisalabad (1.35%, 95% CI: ±1.18) and Sheikhupura (0.68%, 95% CI: ±0.94). The odds of detecting bacterial DNA in soil was increased with a unit increase in organic matter [2.511 (95% CI: 1.453-4.340), p=0.001] and sodium [1.013 (95% CI: 1.005-1.022), p=0.001], whereas, calcium [0.984 (95% CI: 0.975-0.994), p=0.002] and potassium [0.994 (95% CI: 0.990-0.999), p=0.011] had protective effect where a unit increase in each analyte decreased odds for its occurrence by 1.0% approximately. Likewise, for categorical variables (risk factors), the odds of detecting C. burnetii were higher at locations >500m away from a main road [1.95 (95% CI: 1.06-3.78), p=0.04]. The enzyme-linked immunosorbent assay (ELISA) revealed an increased prevalence of antibodies in sheep (17.9%, 95% CI: ±5.54) compared with goats (16.4%, 95% CI: ±4.34). When determining the association between soil DNA and C. burnetii antibodies in small ruminants, the odds of detecting these antibodies were significant in sheep at the livestock barns [2.81 (95% CI: 1.20-7.37), p=0.02]. The IS1111 gene-based sequence analysis revealed a clustering of the DNA into two distinct groups with much genetic divergence (0.76-68.70%): the first group that contained sequences from Lahore district clustered with human and buffalo origin isolates, whereas the second group that contained the sequences from the remaining study districts clustered with goat-, rodent- and human-origin isolates. This study provides the first evidence of the presence of C. burnetii in the environment in Punjab province, Pakistan. Future studies are needed to ascertain the bacteria's molecular epidemiology over a wide geographical area, type the isolates, and evaluates the potential risks to human populations, particularly farmers and veterinarians.