Screening for infectious and neglected tropical diseases among newly arrived migrants from Africa and Asia: a retrospective study from Verona province, Italy

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Ensuring adequate healthcare for newly arrived migrants includes the prevention and management of infectious diseases. This study aimed to estimate the prevalence of selected infections among migrants in northern Italy. Methods We conducted a retrospective cross-sectional study at the Department of Infectious - Tropical Diseases and Microbiology (DITM) of the IRCCS Sacro Cuore Don Calabria Hospital, Negrar di Valpolicella (Verona, Italy) between January 2023 and May 2024. Asylum seekers and undocumented migrants aged ≥ 14 years who had arrived within the previous six months from Africa or Asia were screened for tuberculosis (TB), HIV, hepatitis B (HBV), hepatitis C (HCV), syphilis, strongyloidiasis, schistosomiasis, other intestinal helminthic infections, and filariasis. Diagnostic methods comprised serological, microscopic, molecular, and imaging techniques, applied as appropriate. Results Among the 674 migrants screened (median age: 25 years; 86.4% male), TB infection was detected in 25.4%, and 2.9% were diagnosed with TB disease. HIV prevalence was 1.5%, primarily among individuals from sub-Saharan Africa. Chronic HBV infection was identified in 6.1% of participants, while 55.1% were seronegative and thus eligible for vaccination. Helminthic infections were found in 12.3%, mainly strongyloidiasis and schistosomiasis. Eosinophilia was present in 18.3% and was significantly associated with helminthic infections. Conclusions These findings underscore the persistent burden of infectious diseases among migrant populations and support the implementation of geographically tailored screening programs to improve early detection and public health outcomes. Migrants Screening Tuberculosis Helminths Schistosomiasis Strongyloidiasis Figures Figure 1 Background Over the last decade, international migration has increased across all United Nations (UN) regions, with the most significant growth observed in Europe and Asia [ 1 ]. In Europe alone, the number of international migrants rose by nearly 16%, from approximately 75 million in 2010 to 87 million in 2020 [ 1 ]. Italy has experienced fluctuating migration flows during this period. Between 2014 and 2017, the country saw a sharp increase in sea arrivals, often referred to in political and media discourse as the “refugee crisis” [ 2 ]. The peak was recorded in 2016, with 181,436 migrants arriving by sea. However, from 2018 onward, arrivals declined significantly before rebounding in 2020. In both 2022 and 2023, over 100,000 migrants reached Italy, driven mainly by increased flows from North and Central Africa, as well as a steady rise in arrivals from Asian countries such as Bangladesh and Pakistan [ 2 ]. The health implications of migration have been a focus of public health policies within the European Union/European Economic Area (EU/EEA). In 2018, the European Centre for Disease Prevention and Control (ECDC) published Public Health Guidance on screening and vaccination for infectious diseases in newly arrived migrants, recommending screening for tuberculosis (TB), tuberculosis infection (TBI), human immunodeficiency virus (HIV), hepatitis B (HBV), hepatitis C (HCV), schistosomiasis, and strongyloidiasis [ 3 ]. Early detection and treatment are essential both for individual health—preventing disease progression and late complications—and for public health, by reducing transmission in host countries [ 3 ]. Several infectious diseases relevant to migrant populations can have severe long-term consequences if left untreated. Communicable diseases such as TB, viral hepatitis, HIV, and syphilis pose transmission risks, while non-communicable infections like strongyloidiasis, schistosomiasis, and filariasis may lead to chronic conditions associated with significant morbidity [ 4 , 5 ]. For instance, schistosomiasis can lead to chronic urogenital, hepato-intestinal, and central nervous system complications, while Strongyloides stercoralis infection may cause disseminated disease or fatal hyperinfection in immunosuppressed patients [ 6 ]. Moreover, certain infections carry a risk of local transmission in the EU/EEA, either through organ transplantation (e.g. strongyloidiasis) or via environmental conditions that support the intermediate host, as seen in recent autochthonous cases of urinary schistosomiasis in Corsica, France [ 6 , 7 ]. Importantly, many of these conditions are treatable with short, well-tolerated outpatient regimens, reinforcing the value of systematic screening [ 5 ]. Screening protocols for infectious diseases among newly arrived migrants are crucial for identifying and managing infections that, while uncommon in the host country, may have significant epidemiological and clinical implications. A previous study conducted at the Department of Infectious - Tropical Diseases and Microbiology (DITM) assessed the prevalence of a series of infectious diseases among asylum seekers temporarily residing in Verona province between April 2014 and June 2015 [ 8 ]. The findings highlighted the importance of including helminthic infections in screening strategies, given their prevalence and the favorable safety profile of available treatments [ 8 ]. Tracking changes in the prevalence of infectious diseases among migrants from different regions over time is essential for refining and validating current screening strategies. This study aims to estimate the prevalence of a range of infectious diseases, both communicable and non-communicable, in a cohort of recently arrived asylum seekers and undocumented migrants in Italy. The study focused on infections and diseases of public health relevance, including: TB infection (TBI), HIV infection, viral hepatitis (HBV and HCV), syphilis, strongyloidiasis, schistosomiasis, other intestinal helminthic infections, and filariasis. Additionally, as a secondary objective, we will explore the predictive role of eosinophilia in the context of the screening, analyzing its association with helminthic infections. Methods Study design This was a retrospective observational cross-sectional study analyzing data from infectious disease screening activities conducted at the Department of Infectious - Tropical Diseases and Microbiology (DITM) of the IRCCS Sacro Cuore Don Calabria Hospital, Negrar di Valpolicella (Verona, Italy) from January 2023 to May 2024. Given its retrospective nature, the study did not involve follow-up of participants but rather aimed to describe the prevalence of infectious diseases among recently arrived migrants. Study population and setting The study population included asylum seekers and undocumented migrants aged ≥ 14 years who had arrived within the past six months from Africa and Asia and attended the dedicated outpatient service at DITM for medical screening. Individuals were either referred by local reception centers or presented spontaneously at the outpatient service. Access to screening was granted regardless of the presence or absence of symptoms. Demographic data were collected from official documents issued by the local prefectures where the individuals had applied for asylum. For undocumented migrants, available personal data were obtained from any documents they had at the time of screening. Study procedures All migrants underwent a general medical examination. In addition to a full blood cell count (FBC), diagnostic tests for specific infections were proposed. TB screening was conducted using the QuantiFERON-TB Gold In-Tube (QFT-GIT) assay (LIAISON® QuantiFERON®-TB Gold Plus, DiaSorin) and chest X-rays. HIV screening was performed with an indirect immunoenzymatic assay (HIV Combo V2 Immunoassay System, Biorad), and a Western blot (INNO-LIA, Fujirebio Diagnostics) was used as a confirmatory test. HBV screening was conducted using the following assays: a qualitative immunoenzymatic assay for HBV core antibody, a quantitative chemiluminescence immunoassay (CLIA) for HBV surface antibody, and a qualitative CLIA for HBV surface antigen (Access HBcAb, Access HBsAb, Access HBsAg, Beckman Coulter). HCV serology was detected with CLIA (Access anti-HCV, Beckman Coulter). Syphilis screening was conducted using CLIA for Treponema pallidum , with confirmation by the T. pallidum haemagglutination assay (TPHA) (LIAISON® Treponema Screen, DiaSorin) and the Rapid Plasma Reagin (RPR) test (Mascia Brunelli S.p.A.). Helminthic infections were assessed using the following methods: Stool microscopy for ova and parasites after formol-ether concentration. Urine microscopy after micropore filtration for Schistosoma haematobium (only for individuals from sub-Saharan Africa). Serology for Schistosoma spp. (Schistosoma mansoni ELISA kit, Bordier Affinity Products SA) and/or immunochromatographic test kit ICT Bordier Affinity Products SA. Additionally, urine from selected patients was tested for Schistosoma spp. using in-house PCR. Strongyloides stercoralis infection was screened by serology (in-house immunofluorescence assay [IFAT] and/or ELISA kit, Bordier Affinity Products SA). Stools from subjects with positive serology were also tested by agar plate culture (APC). Filaria spp. infection was screened in migrants from sub-Saharan Africa using serology (Acanthoecheilonema viteae IgG ELISA kit, Bordier Affinity Products SA). All patients with positive Filaria serology underwent additional testing for daytime and/or nighttime microfilaremia. Additionally, stool samples from selected patients, based on clinical evaluation, were tested by in-house PCR amplification for the following parasites: Strongyloides spp., Schistosoma spp., Hymenolepis nana , Dientamoeba spp., Giardia intestinalis , Blastocystis spp., Entamoeba histolytica , Entamoeba dispar , Cryptosporidium spp., Ascaris lumbricoides , Ancylostoma duodenale , Necator americanus , and Trichuris trichiura . Results were recorded anonymously in an Excel database. Variables Key study variables included demographic data, clinical findings, and laboratory results. Eosinophilia was defined as an absolute eosinophil count ≥ 400 cells/µL. Positivity for HIV, HBV, HCV, and syphilis was assessed via serological testing; chronic HBV infection was identified by HBsAg positivity. TBI was diagnosed in individuals with a positive QFT-GIT test, who showed no signs or symptoms of TB disease and had a negative chest X-ray. TB disease was defined based on imaging findings (e.g., chest X-ray for pulmonary TB and other imaging modalities for extrapulmonary TB) compatible with clinical tuberculosis, regardless of the presence or absence of symptoms. Subclinical and symptomatic TB were not distinguished and were both included under this definition. Previously treated TB was defined as a history of disease based on self-reported prior treatment and/or radiological findings suggestive of past TB sequelae, such as fibrotic lesions or calcifications, in the absence of symptoms. Strongyloidiasis was defined by a positive serology and at least one positive fecal test. Schistosomiasis was defined by a positive serology and at least one positive fecal or urinary test. Filariasis was defined by a positive serology and the presence of microfilaremia. Intestinal helminthic infections were defined by the detection of parasites in fecal samples, either through stool microscopy or PCR-based techniques. Missing data were recorded and analyzed, with descriptive statistics used to assess their potential impact on the results. Sample size A convenient sample of all eligible records of migrants screened between January 2023 and May 2024 were considered for analysis. Statistical analysis Diagnostic test results were categorized as binary (positive/negative), while for continuous variables, median and interquartile ranges (IQR) were reported. Frequencies and percentages were reported for categorical variables. The primary outcome was the prevalence of the infections of interest. Prevalence was expressed as the frequency of positive tests over the total number of cases tested, and reported with 95% confidence intervals calculated using the Clopper and Pearson formula. Comparisons between proportions were made using Fisher exact test or Chi square test. A multivariable Firth logistic regression model was used to assess potential risk factors of parasite infections ( S . stercoralis , T. trichiura , hookworm, Schistosoma spp. and Filaria spp.) for eosinophilia, separately for Asia and sub-Saharan Africa, and adjusted for age and sex. Estimates were reported as odds ratios (OR) and 95% confidence intervals (CI). P-values lower than 0.05 were considered significant. Analyses were performed using R software version 4.4.2. Ethical considerations As this was a retrospective study based on anonymized routinely collected data, no individual consent was required. The study protocol received ethical clearance from the ethics committee for clinical trials in the province of Verona and Rovigo (Comitato Etico per la sperimentazione Clinica delle Province di Verona e Rovigo) on the 2nd of July 2024 (protocol number 29). Results Overall, 674 individuals were screened and included in the analysis. The median age was 25 years (IQR 20-31) and 86.4% (n= 582) was male. As regards the geographic area of origin, 52.2% (n= 352) came from sub-Saharan Africa, 35.3% (n=238) originated from Asia, and 12.5% (n=84) from North Africa. Figure 1 shows the number of participants from each country of origin. The median time spent in Italy was 3 months (IQR 1 - 5). Demographic characteristics of participants by macro-area are reported in Table 1. Viral infections Of the 672 participants screened for HIV, 10 (1.5%) tested positive. Nine were from sub-Saharan Africa (9/10; 90%) and one from Bangladesh (1/10; 10%). A total of 673 migrants were screened for HBV infection. Of these, 371 (55.1%) had negative serology and were therefore eligible for vaccination, including 124 out of 352 from sub-Saharan Africa (35.2% of individuals from this region), 180 out of 237 from Asia (75.9%), and 67 out of 84 from North Africa (79.8%). Forty-one individuals (6.1%) tested positive for HBsAg, indicating chronic HBV infection. The majority were from sub-Saharan Africa (31/352; 8.8% of migrants from this region), followed by Asia (9/237; 3.8%) and North Africa (1/84; 1.2%). Of the 658 migrants tested for HCV, five (0.8%) tested positive. One was from sub-Saharan Africa (1/339; 0.3% of individuals from this region), three from Asia (3/235; 1.3%), and one from North Africa (1/84; 1.2%). Bacterial infections Out of 635 individuals tested for syphilis, 13 (2.0%) were positive. Of these, 12 were from sub-Saharan Africa (12/341; 3.5% of migrants from this region), one from Asia (1/213; 0.5%), and none from North Africa (0/81; 0.0%). A total of 653 migrants were screened for tuberculosis using QFT-GIT: 188 (28.8%) tested positive, 460 (70.4%) negative, and five (0.8%) had indeterminate results. Among the 188 QFT-positive individuals, 170 underwent chest X-ray, which revealed 160 cases (24.5%) of tuberculosis infection (TBI). Two individuals (0.3%) had previously treated TB, and eight (1.2%) were diagnosed with TB disease (Table 2). For the purposes of this study, we did not differentiate between subclinical and symptomatic presentations of TB disease. Helminthic Infections At least one stool sample for microscopy was provided by 618 (91.7%) subjects, of whom 333 out of 352 (94.6%) from sub-Saharan Africa, 213 out of 238 (89.5%) from Asia, and 72 out of 84 (85.7%) from North Africa. A significant association was detected between geographical region and positivity at stool microscopy (chi-squared test, p-value<0.001). Of the 642 samples examined by either stool microscopy or PCR, 79 (12.3%) were positive for at least one helminth. Most positive individuals were from sub-Saharan Africa (62, 78.5%), followed by Asia (14, 17.7%) and North Africa (3, 3.8%). Data concerning the results of stool microscopy are summarized in Table 3. Strongyloides stercoralis was detected by a number of tests, including serology, APC and PCR. Table 4 displays the results of all screening tests used, per geographical origin. While the number of positive S. stercoralis serology tests was significantly larger among individuals from Asia compared to the other geographical areas, figures did not significantly differ per geographical origin when considering all stool tests. Overall, 9 out of 673 individuals were positive to at least one fecal test for S. stercoralis : three from sub-Saharan Africa, and six from Asia (Table 4). The prevalence of strongyloidiasis, defined as a positive serology and at least one positive fecal test, was 1.3% (95% CI: 0.6% - 2.5%). Similarly, different assays were used for the screening of schistosomiasis, including serology for all forms of infection and diagnostics on stool and urine, targeting intestinal and urinary schistosomiasis, respectively (Table 5). Overall, 50 out of 388 participants was positive to at least one fecal or stool test, all from sub-Saharan Africa. Thus, the prevalence of schistosomiasis, defined as a positive serology and at least one positive fecal or urinary test, was 12.9% (95% CI: 9.7% - 16.6%). Further, 332 individuals from sub-Saharan Africa were tested with the pan-filaria serology. Twenty-three individuals out of the 332 (6.9%) were positive, so were tested for microfilaremia. The latter was positive in six (26.1%) out of the 23 serology-positive individuals, permitting the diagnosis of two Loa loa and four Mansonella perstans cases. The prevalence of filariasis, defined by a positive serology and the presence of microfilaremia, was 1.8% (95% CI: 0.7% - 3.9%). Eosinophilia The median eosinophil count was 200/µL (IQR 100-300) in the whole cohort, including 21% subjects (n=141) with an eosinophil count ≥400/µL. Median eosinophil count in individuals from sub-Saharan Africa was 200 (IQR 100-300). For Asia, median eosinophil count was 200 (IQR 100-400). Median eosinophil count of people from North Africa was 100 (IQR 100-300). As for eosinophilia by geographical region of origin, it was present in 64 of 351 (18.2%) individuals from sub-Saharan Africa (median eosinophil count 600 (IQR: 500-900)), 64 of 238 (26.9%) individuals from Asia (median eosinophil count 500 (IQR 400-800)), 13 of 84 (15.5%) subjects from North Africa (median eosinophil count 500 (IQR: 400-600)). The multivariable model for sub-Saharan Africa found a significant association between eosinophilia and schistosomiasis (OR 4.31, 95%CI 2.10-8.84, p<0.001). For Asia, eosinophilia was significantly associated with strongyloidiasis (OR 8.11, 95%CI 1.44-82.6, p=0.017) and with hookworm (OR 29.5, 95%CI 3.26-3,891, p<0.001). As regards the sub-group of individuals from North Africa, models were not possible due to the extremely low frequency of parasitic infections diagnosed. Discussion The first notable finding from our study is the significant shift in the geographical origin of migrants. The proportion of migrants from Asia has increased to 35.3%, compared to 21% in our previous study (p < 0.001) [ 8 ]. This shift aligns with global migration trends and the most recent Italian estimates [ 1 , 2 ]. Such a change in the geographical origin of migrants should be considered when adapting guidelines and recommendations for screening both infectious and non-infectious diseases to the evolving epidemiological landscape. In this context, our study offers an updated overview of the prevalence of infectious diseases among recently arrived migrants in Italy, nine years after our previous work in the same setting [ 8 ]. The findings further confirm the relevance of infectious diseases in this population, with significant differences observed based on migrants' geographical origin. HIV prevalence among migrants in this study was relatively low, with an overall rate of 1.5%, which is comparable to the prevalence observed in our previous study (1.3%) [ 8 ]. Similarly, there was a notable geographic disparity, with the majority of cases being observed among migrants from sub-Saharan Africa (90%). This is consistent with ECDC estimates as well as previous studies showing the highest HIV prevalence rates in sub-Saharan Africa, highlighting the continued need for comprehensive HIV screening and awareness programs targeting individuals from that geographical area [ 9 , 10 ]. The low prevalence observed among migrants from Asia and North Africa suggests that a targeted approach might be sufficient in those populations, rather than universal screening. Regarding HBV infection, 6.1% of participants were positive for HBsAg. Of note, HBsAg positivity in our study was lower than both our previous work (i.e. 11.6%) and similar studies on migrant populations [ 11 ]. Additionally, 55.1% of individuals had negative HBV serology, indicating a substantial proportion of susceptible individuals who could benefit from vaccination programs. In particular, 75.9% of Asian migrants and 79.8% of North African migrants were eligible for HBV vaccination, emphasizing the need for tailored immunization strategies. Although the overall prevalence of HCV in our cohort was low (0.8%), it remains noteworthy, particularly among individuals from sub-Saharan Africa and Asia. The prevalence observed in our study is lower than what has been reported in the literature but is consistent with our data from 2014–2015 [ 12 ]. However, this emphasizes the importance of ongoing surveillance, as even low prevalence rates can allow for early detection and intervention, preventing long-term complications such as liver cirrhosis and hepatocellular carcinoma. Syphilis was detected in 2% of the migrants, which is consistent with findings from other studies that have addressed sexual health within migrant populations [ 13 ]. The prevalence was particularly high among sub-Saharan African migrants (3.5%) and relatively low in migrants from Asia and North Africa. In our previous study, 4.5% of participants from sub-Saharan Africa and 1.0% of those from Asia tested positive. This emphasizes the need for continued vigilance in screening for sexually transmitted infections, particularly in populations with higher rates of sexual risk behaviors and prior exposure in endemic regions. Tuberculosis emerged as one of the most concerning findings in our study. The prevalence of TBI was 24.5%, while TB disease was diagnosed in 1.2% of participants, including both pulmonary and extrapulmonary forms. These results underscore the importance of comprehensive diagnostic strategies for TB among newly arrived migrants. The rate of TBI is consistent with epidemiological data from high-burden regions such as sub-Saharan Africa and Asia [ 14 – 17 ], from which most of our cohort originated. These findings reinforce the need to maintain systematic TB screening upon arrival in Europe and to initiate preventive treatment for TBI, which is essential to reduce the risk of disease reactivation and subsequent transmission within host countries. A particularly relevant aspect of our study concerns helminthic infections. We observed an overall proportion of 12.3% for at least one helminthic infection diagnosed through a positive stool test and/or urine test, with clear differences by geographical region. The prevalence of strongyloidiasis was 1.3%, which is consistent with the stool-based prevalence reported by Asundi et al. (1.8%) [ 18 ]. Our study also highlights a significant seroprevalence of strongyloidiasis (7.2%), with seropositivity markedly higher among Asian migrants (13.6%). Notably, our findings are lower than the pooled seroprevalence of 12.2% reported by Asundi et al. [ 18 ]. It should be noted that different serological assays have a wide range of sensitivity and specificity values, with most concerns relating the potential cross-reactivity with other nematodes [ 18 , 19 ]. However, due to the potential development of severe or disseminated infection in cases of immunocompromise, treatment of individuals who are only positive for serology is considered justified. Therefore, in this setting, lower specificity is not regarded as problematic as lower sensitivity. The prevalence of schistosomiasis was 12.9%, with all cases, as expected, found among migrants from sub-Saharan Africa. It is worth noting that our findings are higher than the stool-based prevalence of 0.95% and the urine-based prevalence of 6.8% reported by Asundi et al. [ 18 ]. Also, the seroprevalence for Schistosoma spp. in our cohort was higher (52.6%) than that reported by Asundi et al. (18.4%), likely reflecting the low specificity of the test and the need for alternative diagnostic approaches for schistosomiasis, similarly to strongyloidiasis [ 18 ]. Filariasis remains an underdiagnosed parasitic disease in migrant populations, with limited data available in non-endemic settings [ 20 ]. Data on the prevalence of filariasis among migrants in Europe remain scarce, and most available epidemiological evidence comes from studies conducted in endemic regions of Africa [ 21 , 22 ]. This knowledge gap complicates the development of targeted screening strategies in migrant populations, particularly given the clinical implications of filarial infections. Loiasis has recently been associated with increased mortality in cases with a high microfilarial burden, with eyeworm and Calabar swellings as characteristic clinical features; however, the disease can also present with atypical, non-specific symptoms [ 23 ]. While infection with M. perstans is generally considered less severe than other filarial infections, it can still lead to long-term symptoms and complications in certain individuals, such as abdominal pain and dermatitis [ 24 ]. Moreover, the stool tests for other parasitic diseases, including hookworm and T. trichiura , revealed significant rates of infection, particularly among migrants from Asia. These findings confirm that routine screening for helminths is key a component of migrant health assessments, especially since these infections are often asymptomatic in the early stages but can lead to severe health consequences if untreated [ 3 , 4 , 8 ]. The cost-effectiveness and ease of treatment for these parasitic infections further emphasize the importance of including them in national screening protocols for newly arrived migrants. Eosinophilia was present in 18.3% of the screened migrants and was significantly associated with helminthic infections. This association was especially pronounced among migrants from sub-Saharan Africa and Asia. Our analysis confirmed that S. stercoralis and Schistosoma spp. were the most frequently associated parasites, in line with previous studies [ 25 , 26 ]. Specifically, eosinophilia was observed in 18.2% of African migrants and 26.9% of Asian migrants, with the condition predominantly linked to schistosomiasis in African migrants and strongyloidiasis in Asian migrants. The sensitivity of eosinophilia as a marker for helminthiasis is well recognized, but its specificity remains low, as it can be influenced by non-infectious conditions such as allergies and autoimmune diseases [ 25 , 27 ]. Remarkably, our findings suggest that eosinophilia alone is insufficient to rule out helminthic infections. Among S. stercoralis cases, 2/9 (22.2%) of infected individuals did not present eosinophilia, emphasizing the need for systematic screening. Similarly, 27/50 (54.0%) patients with Schistosoma spp. infections did not have eosinophilia, suggesting that chronic infections may not always trigger a sustained eosinophilic response [ 28 ]. These results highlight the importance of a combined diagnostic approach, integrating eosinophilia assessment with direct parasitological methods, serology, and molecular techniques to improve case detection. One of the main limitations of our study is its retrospective nature, which may have affected the quality of data collection. A comparison of prevalence with data from previous studies is challenging due to differences in the definitions of helminthic infections and the use of various diagnostic tests for screening (e.g., different serological assays for S. stercoralis and Schistosoma spp.). Additionally, the collinearity between eosinophilia and the presence of certain parasites posed a challenge in constructing robust multivariable models to assess risk factors, as reflected in the wide confidence intervals of the OR estimates. Furthermore, our findings reflect the specific characteristics of the local migrant population, which may limit their applicability to other settings with different demographic and epidemiological profiles. Additionally, the distinction between asylum seekers and undocumented migrants was not addressed in the paper, and no analysis was performed to explore potential differences between these two categories. Finally, with regard to TB classification, we did not distinguish between subclinical and symptomatic forms of TB [ 29 ], as this distinction was beyond the scope and focus of the present study. Conclusions Our findings support the need for a tailored approach to screening for infectious diseases in migrants, adapting strategies based on geographical origin. The integration of effective screening protocols and expanded access to vaccination and early treatment could significantly improve both individual and public health outcomes. Helminthic infections, particularly S. stercoralis and Schistosoma spp., remain highly prevalent, and eosinophilia alone is not a sufficient screening tool. Systematic, evidence-based screening programs are essential to ensure early detection and treatment, reducing the burden of infectious diseases in migrant populations and preventing long-term complications. Declarations Acknowledgements We would like to thank the nurses, medical doctors, and laboratory staff at the DITM for their dedication to migrant care. We are also grateful to all the study participants. Author contribution TU: Conceptualization, Methodology, Investigation, Data curation, Project administration, Visualization, Writing – original draft, Writing – review and editing. LB: Investigation, Data curation, Visualization, Writing – review and editing. AZ: Investigation, Data curation, Writing – review and editing. CM : Formal analysis, Writing – original draft, Writing – review and editing. PC: Investigation, Writing – review and editing. ES: Investigation, Writing – review and editing. LM : Investigation, Writing – review and editing. FG: Conceptualization, Methodology, Supervision, Writing – review and editing. DB : Conceptualization, Methodology, Supervision, Writing – original draft, Writing – review and editing. Funding This work was partly funded by the Italian Ministry of Health (Ricerca corrente Linea L3P1) with funds to IRCCS Sacro Cuore Don Calabria Hospital. The funding source had no role in study design, writing, and submission. Availability of data and materials The data underlying this article will be shared on reasonable request to the corresponding author. Ethics approval The study protocol received ethical clearance from the ethics committee for clinical trials in the province of Verona and Rovigo (Comitato Etico per la sperimentazione Clinica delle Province di Verona e Rovigo) on the 2 nd of July 2024 (protocol number 29). Competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. References McAuliffe M, Oucho LA, editors. World migration report 2024. Geneva: International Organization for Migration; 2024. Available from: https://publications.iom.int/books/world-migration-report-2024 [accessed 5 Apr 2025]. Centro Studi e Ricerche IDOS. Dossier statistico immigrazione 2024. Rome: Edizioni IDOS; 2024. 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Tamarozzi F, Buonfrate D, Ricaboni D, Ursini T, Foti G, Gobbi F. Spleen nodules in Loa loa infection: re-emerging knowledge and future perspectives. Lancet Infect Dis. 2022;22:e197–206. https://doi.org/10.1016/S1473-3099(21)00632-0 . Boussinesq M. Loiasis. Ann Trop Med Parasitol. 2006;100:715–31. https://doi.org/10.1179/136485906X112194 . Salzer HJF, Rolling T, Vinnemeier CD, Tannich E, Schmiedel S, Addo MM, et al. Helminthic infections in returning travelers and migrants with eosinophilia: diagnostic value of medical history, eosinophil count and IgE. Travel Med Infect Dis. 2017;20:49–55. https://doi.org/10.1016/j.tmaid.2017.09.001 . Ding A, Osorio M, Teferi M, Gallo Marin B, Cruz-Sánchez M, Lorenz M, et al. A retrospective longitudinal study of refugees with eosinophilia at an academic center in the United States from 2015 to 2020. Open Forum Infect Dis. 2024;11:ofae430. https://doi.org/10.1093/ofid/ofae430 . Folci M, Ramponi G, Arcari I, Zumbo A, Brunetta E. Eosinophils as major player in type 2 inflammation: autoimmunity and beyond. Adv Exp Med Biol. 2021;1347:197–219. https://doi.org/10.1007/5584_2021_640 . O'Connell EM, Nutman TB. Eosinophilia in infectious diseases. Immunol Allergy Clin North Am. 2015;35:493–522. https://doi.org/10.1016/j.iac.2015.05.003 . Migliori GB, Ong CWM, Petrone L, D'Ambrosio L, Centis R, Goletti D. The definition of tuberculosis infection based on the spectrum of tuberculosis disease. Breathe (Sheff). 2021;17:210079. https://doi.org/10.1183/20734735.0079-2021 . Tables Table 1. Demographic Characteristics of Study Participants Region Overall Sub-Saharan Africa Asia North Africa N=674 N=352 N=238 N=84 Median age in years (IQR) 25 (20-31) 23 (19-29) 27 (23-34) 24 (18-32) Male, n (%) 582 (86.4%) 284 (80.9%) 223 (93.7%) 75 (89.3) Median number of months in country (IQR) 3 (1-5) 2 (1-5) 3 (2-5) 2 (1-6) Table 2. Tuberculosis screening results Region p-value* Overall Sub-Saharan Africa Asia North Africa <0.001 Negative n (%) 460 (70.4%) 207 (61.2%) 181 (78.3%) 72 (85.7%) TBI n (%) 160 (24.5%) 111 (32.8%) 43 (18.6%) 6 (7.1%) Previously treated TB n (%) 2 (0.3%) 1 (0.3%) 0 (0.0%) 1 (1.2%) PTB n (%) 5 (0.8%) 2 (0.6%) 3 (1.3%) 0 EPTB n (%) 3 (0.5%) 2 (0.6%) 1 (0.4%) 0 Missing n 21 14 7 0 * Fisher’s exact test TBI: Tuberculosis infection; PTB: Pulmonary TB; EPTB: Extrapulmonary TB Table 3. Stool microscopy results Region Overall Sub-Saharan Africa Asia North Africa Individuals screened by stool microscopy 618 333 213 72 Positive for S. stercoralis larvae n (%) 3 (0.5%) 1 (0.3%) 2 (0.9%) 0 Positive for S. mansoni eggs n (%) 28 (4.5%) 28 (8.4%) - 0 Positive for hookworm 1 eggs n (%) 12 (1.9%) 6 (1.8%) 6 (2.8%) 0 Positive for A. lumbricoides eggs n (%) 1 (0.2%) 1 (0.3%) 0 0 Positive for T. trichiura eggs n (%) 6 (1.0%) 0 6 (2.8%) 0 Positive for other parasites 2 n (%) 244 (39.5%) 163 (48.9%) 57 (26.8%) 24 (33.3%) 1 Includes Ancylostoma duodenale and Necator americanus 2 Reporting is focused on helminths determined to be clinically relevant, such as soil-transmitted helminths. Some other parasites, both helminths and protozoa, might not have a clinical relevance and are included in the other parasites group (e.g. Hymenolepis nana and Endolimax nana ). Table 4. Strongyloides stercoralis results Region p-value* Overall Sub-Saharan Africa Asia North Africa Serology <0.001 Individuals screened by serology n 671 351 204 82 Negative n (%) 623 (92.8%) 337 (96.0%) 204 (86.4%) 82 (97.6%) Positive n (%) 48 (7.2%) 14 (4.0%) 32 (13.6%) 2 (2.4%) Stool PCR 0.5 Individuals screened by stool PCR n 142 66 57 19 Negative n (%) 138 (97.2%) 65 (98.5%) 55 (96.5%) 18 (94.7%) Positive n (%) 4 (2.8%) 1 (1.5%) 2 (3.5%) 1 (5.3%) Stool microscopy 0.7 Individuals screened by stool microscopy n 618 333 213 72 Negative n (%) 615 (99.5%) 332 (99.7%) 211 (99.1%) 72 (100.0%) Positive n (%) 3 (0.5%) 1 (0.3%) 2 (0.9%) 0 APC >0.9 Individuals screened by APC n 30 11 18 1 Negative n (%) 21 (70.0%) 8 (72.7%) 12 (66.7%) 1 (100.0%) Positive n (%) 9 (30.0%) 3 (27.3%) 6 (33.3%) 0 Missing n 644 341 220 83 *Pearson’s Chi-squared test; Fisher’s exact test Table 5. Schistosoma spp. results Region p-value* Overall Sub-Saharan Africa North Africa Serology 0.084 Individuals screened by serology n 386 350 36 Negative n (%) 183 (47.4%) 161 (46.0%) 22 (61.1%) Positive n (%) 203 (52.6%) 189 (54.0%) 14 (38.9%) Stool PCR 0.5 Individuals screened by stool PCR n 75 66 9 Negative n (%) 69 (92.0%) 61 (92.4%) 8 (88.9%) Positive n (%) 6 (8.0%) 5 (7.6%) 1 (11.1%) Stool microscopy 0.2 Individuals screened by stool microscopy n 364 333 31 Negative n (%) 336 (92.3%) 305 (91.6%) 31 (100.0%) Positive n (%) 28 (7.7%) 28 (8.4%) 0 Urine PCR Individuals screened by urine PCR n 19 19 0 Negative n (%) 19 (100.0%) 19 (100.0%) 0 Positive n (%) 0 (0.0%) 0 (0.0%) 0 Urine microscopy 0.2 Individuals screened by urine microscopy n 355 322 33 Negative n (%) 335 (94.4%) 302 (93.8%) 33 (100.0%) Positive n (%) 20 (5.6%) 20 (6.2%) 0 Missing n 81 30 51 *Pearson’s Chi-squared test; Fisher’s exact test Additional Declarations No competing interests reported. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6930017","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":477645596,"identity":"efbacd7e-d410-422a-b3e8-d55f144759e3","order_by":0,"name":"Tamara Ursini","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABB0lEQVRIiWNgGAWjYHADxgaGhApkAWbs6nhQtZxB0YJdDw8Kj7ENhYtdiz376cTPFTUMidv7D7c9eDivTp5/9uGDn3kq7skxsPMfwGoLT+5myTPHGBLn3EhsN0jcdthwxrm0ZGmeM8XGuB2Wu0GygY0hcYYEY5tE4rYDjBt4eMyYedsSEhtwaeF/u/lnwz+gFv6DQC1z6uxhWupxapHI3SbZ2AbUwpAI1NLAnAjTkoDTYTfebrNs7JMwniEB1JJw7HDyjDNsyZJzziQYtjEzG2DTwt6fu/lmwzcb2Rn8x59J/qips+3vYT744U1Fgjw//8EHWK2BAAksYmx41I+CUTAKRsEowA8AhlxVxY7jqO4AAAAASUVORK5CYII=","orcid":"","institution":"Department of Infectious - 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In Europe alone, the number of international migrants rose by nearly 16%, from approximately 75\u0026nbsp;million in 2010 to 87\u0026nbsp;million in 2020 [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eItaly has experienced fluctuating migration flows during this period. Between 2014 and 2017, the country saw a sharp increase in sea arrivals, often referred to in political and media discourse as the \u0026ldquo;refugee crisis\u0026rdquo; [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. The peak was recorded in 2016, with 181,436 migrants arriving by sea. However, from 2018 onward, arrivals declined significantly before rebounding in 2020. In both 2022 and 2023, over 100,000 migrants reached Italy, driven mainly by increased flows from North and Central Africa, as well as a steady rise in arrivals from Asian countries such as Bangladesh and Pakistan [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe health implications of migration have been a focus of public health policies within the European Union/European Economic Area (EU/EEA). In 2018, the European Centre for Disease Prevention and Control (ECDC) published Public Health Guidance on screening and vaccination for infectious diseases in newly arrived migrants, recommending screening for tuberculosis (TB), tuberculosis infection (TBI), human immunodeficiency virus (HIV), hepatitis B (HBV), hepatitis C (HCV), schistosomiasis, and strongyloidiasis [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Early detection and treatment are essential both for individual health\u0026mdash;preventing disease progression and late complications\u0026mdash;and for public health, by reducing transmission in host countries [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eSeveral infectious diseases relevant to migrant populations can have severe long-term consequences if left untreated. Communicable diseases such as TB, viral hepatitis, HIV, and syphilis pose transmission risks, while non-communicable infections like strongyloidiasis, schistosomiasis, and filariasis may lead to chronic conditions associated with significant morbidity [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. For instance, schistosomiasis can lead to chronic urogenital, hepato-intestinal, and central nervous system complications, while \u003cem\u003eStrongyloides stercoralis\u003c/em\u003e infection may cause disseminated disease or fatal hyperinfection in immunosuppressed patients [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Moreover, certain infections carry a risk of local transmission in the EU/EEA, either through organ transplantation (e.g. strongyloidiasis) or via environmental conditions that support the intermediate host, as seen in recent autochthonous cases of urinary schistosomiasis in Corsica, France [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Importantly, many of these conditions are treatable with short, well-tolerated outpatient regimens, reinforcing the value of systematic screening [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eScreening protocols for infectious diseases among newly arrived migrants are crucial for identifying and managing infections that, while uncommon in the host country, may have significant epidemiological and clinical implications. A previous study conducted at the Department of Infectious - Tropical Diseases and Microbiology (DITM) assessed the prevalence of a series of infectious diseases among asylum seekers temporarily residing in Verona province between April 2014 and June 2015 [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. The findings highlighted the importance of including helminthic infections in screening strategies, given their prevalence and the favorable safety profile of available treatments [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eTracking changes in the prevalence of infectious diseases among migrants from different regions over time is essential for refining and validating current screening strategies. This study aims to estimate the prevalence of a range of infectious diseases, both communicable and non-communicable, in a cohort of recently arrived asylum seekers and undocumented migrants in Italy.\u003c/p\u003e \u003cp\u003eThe study focused on infections and diseases of public health relevance, including: TB infection (TBI), HIV infection, viral hepatitis (HBV and HCV), syphilis, strongyloidiasis, schistosomiasis, other intestinal helminthic infections, and filariasis. Additionally, as a secondary objective, we will explore the predictive role of eosinophilia in the context of the screening, analyzing its association with helminthic infections.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy design\u003c/h2\u003e \u003cp\u003eThis was a retrospective observational cross-sectional study analyzing data from infectious disease screening activities conducted at the Department of Infectious - Tropical Diseases and Microbiology (DITM) of the IRCCS Sacro Cuore Don Calabria Hospital, Negrar di Valpolicella (Verona, Italy) from January 2023 to May 2024. Given its retrospective nature, the study did not involve follow-up of participants but rather aimed to describe the prevalence of infectious diseases among recently arrived migrants.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eStudy population and setting\u003c/h3\u003e\n\u003cp\u003eThe study population included asylum seekers and undocumented migrants aged\u0026thinsp;\u0026ge;\u0026thinsp;14 years who had arrived within the past six months from Africa and Asia and attended the dedicated outpatient service at DITM for medical screening. Individuals were either referred by local reception centers or presented spontaneously at the outpatient service. Access to screening was granted regardless of the presence or absence of symptoms. Demographic data were collected from official documents issued by the local prefectures where the individuals had applied for asylum. For undocumented migrants, available personal data were obtained from any documents they had at the time of screening.\u003c/p\u003e\n\u003ch3\u003eStudy procedures\u003c/h3\u003e\n\u003cp\u003eAll migrants underwent a general medical examination. In addition to a full blood cell count (FBC), diagnostic tests for specific infections were proposed.\u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003eTB screening was conducted using the QuantiFERON-TB Gold In-Tube (QFT-GIT) assay (LIAISON\u0026reg; QuantiFERON\u0026reg;-TB Gold Plus, DiaSorin) and chest X-rays.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eHIV screening was performed with an indirect immunoenzymatic assay (HIV Combo V2 Immunoassay System, Biorad), and a Western blot (INNO-LIA, Fujirebio Diagnostics) was used as a confirmatory test.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eHBV screening was conducted using the following assays: a qualitative immunoenzymatic assay for HBV core antibody, a quantitative chemiluminescence immunoassay (CLIA) for HBV surface antibody, and a qualitative CLIA for HBV surface antigen (Access HBcAb, Access HBsAb, Access HBsAg, Beckman Coulter).\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eHCV serology was detected with CLIA (Access anti-HCV, Beckman Coulter).\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eSyphilis screening was conducted using CLIA for \u003cem\u003eTreponema pallidum\u003c/em\u003e, with confirmation by the \u003cem\u003eT. pallidum\u003c/em\u003e haemagglutination assay (TPHA) (LIAISON\u0026reg; Treponema Screen, DiaSorin) and the Rapid Plasma Reagin (RPR) test (Mascia Brunelli S.p.A.).\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eHelminthic infections were assessed using the following methods:\u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003eStool microscopy for ova and parasites after formol-ether concentration.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eUrine microscopy after micropore filtration for \u003cem\u003eSchistosoma haematobium\u003c/em\u003e (only for individuals from sub-Saharan Africa).\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eSerology for \u003cem\u003eSchistosoma\u003c/em\u003e spp. (Schistosoma mansoni ELISA kit, Bordier Affinity Products SA) and/or immunochromatographic test kit ICT Bordier Affinity Products SA.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eAdditionally, urine from selected patients was tested for \u003cem\u003eSchistosoma\u003c/em\u003e spp. using in-house PCR.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003e \u003cem\u003eStrongyloides stercoralis\u003c/em\u003e infection was screened by serology (in-house immunofluorescence assay [IFAT] and/or ELISA kit, Bordier Affinity Products SA). Stools from subjects with positive serology were also tested by agar plate culture (APC).\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003e \u003cem\u003eFilaria\u003c/em\u003e spp. infection was screened in migrants from sub-Saharan Africa using serology (Acanthoecheilonema viteae IgG ELISA kit, Bordier Affinity Products SA). All patients with positive \u003cem\u003eFilaria\u003c/em\u003e serology underwent additional testing for daytime and/or nighttime microfilaremia.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eAdditionally, stool samples from selected patients, based on clinical evaluation, were tested by in-house PCR amplification for the following parasites: \u003cem\u003eStrongyloides\u003c/em\u003e spp., \u003cem\u003eSchistosoma\u003c/em\u003e spp., \u003cem\u003eHymenolepis nana\u003c/em\u003e, \u003cem\u003eDientamoeba\u003c/em\u003e spp., \u003cem\u003eGiardia intestinalis\u003c/em\u003e, \u003cem\u003eBlastocystis\u003c/em\u003e spp., \u003cem\u003eEntamoeba histolytica\u003c/em\u003e, \u003cem\u003eEntamoeba dispar\u003c/em\u003e, \u003cem\u003eCryptosporidium\u003c/em\u003e spp., \u003cem\u003eAscaris lumbricoides\u003c/em\u003e, \u003cem\u003eAncylostoma duodenale\u003c/em\u003e, \u003cem\u003eNecator americanus\u003c/em\u003e, and \u003cem\u003eTrichuris trichiura\u003c/em\u003e.\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eResults were recorded anonymously in an Excel database.\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e\n\u003ch3\u003eVariables\u003c/h3\u003e\n\u003cp\u003eKey study variables included demographic data, clinical findings, and laboratory results.\u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003eEosinophilia was defined as an absolute eosinophil count\u0026thinsp;\u0026ge;\u0026thinsp;400 cells/\u0026micro;L.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003ePositivity for HIV, HBV, HCV, and syphilis was assessed via serological testing; chronic HBV infection was identified by HBsAg positivity.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eTBI was diagnosed in individuals with a positive QFT-GIT test, who showed no signs or symptoms of TB disease and had a negative chest X-ray.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eTB disease was defined based on imaging findings (e.g., chest X-ray for pulmonary TB and other imaging modalities for extrapulmonary TB) compatible with clinical tuberculosis, regardless of the presence or absence of symptoms. Subclinical and symptomatic TB were not distinguished and were both included under this definition.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003ePreviously treated TB was defined as a history of disease based on self-reported prior treatment and/or radiological findings suggestive of past TB sequelae, such as fibrotic lesions or calcifications, in the absence of symptoms.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eStrongyloidiasis was defined by a positive serology and at least one positive fecal test.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eSchistosomiasis was defined by a positive serology and at least one positive fecal or urinary test.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eFilariasis was defined by a positive serology and the presence of microfilaremia.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eIntestinal helminthic infections were defined by the detection of parasites in fecal samples, either through stool microscopy or PCR-based techniques.\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003cp\u003eMissing data were recorded and analyzed, with descriptive statistics used to assess their potential impact on the results.\u003c/p\u003e\n\u003ch3\u003eSample size\u003c/h3\u003e\n\u003cp\u003eA convenient sample of all eligible records of migrants screened between January 2023 and May 2024 were considered for analysis.\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eDiagnostic test results were categorized as binary (positive/negative), while for continuous variables, median and interquartile ranges (IQR) were reported. Frequencies and percentages were reported for categorical variables. The primary outcome was the prevalence of the infections of interest. Prevalence was expressed as the frequency of positive tests over the total number of cases tested, and reported with 95% confidence intervals calculated using the Clopper and Pearson formula. Comparisons between proportions were made using Fisher exact test or Chi square test. A multivariable Firth logistic regression model was used to assess potential risk factors of parasite infections (\u003cem\u003eS\u003c/em\u003e. \u003cem\u003estercoralis\u003c/em\u003e, \u003cem\u003eT. trichiura\u003c/em\u003e, hookworm, \u003cem\u003eSchistosoma\u003c/em\u003e spp. and \u003cem\u003eFilaria\u003c/em\u003e spp.) for eosinophilia, separately for Asia and sub-Saharan Africa, and adjusted for age and sex. Estimates were reported as odds ratios (OR) and 95% confidence intervals (CI). P-values lower than 0.05 were considered significant. Analyses were performed using R software version 4.4.2.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eEthical considerations\u003c/h3\u003e\n\u003cp\u003eAs this was a retrospective study based on anonymized routinely collected data, no individual consent was required. The study protocol received ethical clearance from the ethics committee for clinical trials in the province of Verona and Rovigo (Comitato Etico per la sperimentazione Clinica delle Province di Verona e Rovigo) on the 2nd of July 2024 (protocol number 29).\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eOverall, 674 individuals were screened and included in the analysis. The median age was 25 years (IQR 20-31) and 86.4% (n= 582) was male. As regards the geographic area of origin, 52.2% (n= 352) came from sub-Saharan Africa, 35.3% (n=238) originated from Asia, and 12.5% (n=84) from North Africa. Figure 1 shows the number of participants from each country of origin.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe median time spent in Italy was 3 months (IQR 1 - 5).\u003c/p\u003e\n\u003cp\u003eDemographic characteristics of participants by macro-area are reported in Table 1.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eViral infections\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eOf the 672 participants screened for HIV, 10 (1.5%) tested positive. Nine were from sub-Saharan Africa (9/10; 90%) and one from Bangladesh (1/10; 10%).\u003c/p\u003e\n\u003cp\u003eA total of 673 migrants were screened for HBV infection. Of these, 371 (55.1%) had negative serology and were therefore eligible for vaccination, including 124 out of 352 from sub-Saharan Africa (35.2% of individuals from this region), 180 out of 237 from Asia (75.9%), and 67 out of 84 from North Africa (79.8%).\u003c/p\u003e\n\u003cp\u003eForty-one individuals (6.1%) tested positive for HBsAg, indicating chronic HBV infection. The majority were from sub-Saharan Africa (31/352; 8.8% of migrants from this region), followed by Asia (9/237; 3.8%) and North Africa (1/84; 1.2%).\u003c/p\u003e\n\u003cp\u003eOf the 658 migrants tested for HCV, five (0.8%) tested positive. One was from sub-Saharan Africa (1/339; 0.3% of individuals from this region), three from Asia (3/235; 1.3%), and one from North Africa (1/84; 1.2%).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eBacterial infections\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eOut of 635 individuals tested for syphilis, 13 (2.0%) were positive. Of these, 12 were from sub-Saharan Africa (12/341; 3.5% of migrants from this region), one from Asia (1/213; 0.5%), and none from North Africa (0/81; 0.0%).\u003c/p\u003e\n\u003cp\u003eA total of 653 migrants were screened for tuberculosis using QFT-GIT: 188 (28.8%) tested positive, 460 (70.4%) negative, and five (0.8%) had indeterminate results. Among the 188 QFT-positive individuals, 170 underwent chest X-ray, which revealed 160 cases (24.5%) of tuberculosis infection (TBI). Two individuals (0.3%) had previously treated TB, and eight (1.2%) were diagnosed with TB disease (Table 2). \u0026nbsp;For the purposes of this study, we did not differentiate between subclinical and symptomatic presentations of TB disease.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eHelminthic Infections\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAt least one stool sample for microscopy was provided by 618 (91.7%) subjects, of whom 333 out of 352 (94.6%) from sub-Saharan Africa, 213 out of 238 (89.5%) from Asia, and 72 out of 84 (85.7%) from North Africa. A significant association was detected between geographical region and positivity at stool microscopy (chi-squared test, p-value\u0026lt;0.001).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eOf the 642 samples examined by either stool microscopy or PCR, 79 (12.3%) were positive for at least one helminth. \u0026nbsp; Most positive individuals were from sub-Saharan Africa (62, 78.5%), followed by Asia (14, 17.7%) and North Africa (3, 3.8%). Data concerning the results of stool microscopy are summarized in Table 3.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eStrongyloides stercoralis\u003c/em\u003e was detected by a number of tests, including serology, APC and PCR. Table 4 displays the results of all screening tests used, per geographical origin. While the number of positive \u003cem\u003eS. stercoralis\u003c/em\u003e serology tests was significantly larger among individuals from Asia compared to the other geographical areas, figures did not significantly differ per geographical origin when considering all stool tests. Overall, 9 out of 673 individuals were positive to at least one fecal test for \u003cem\u003eS. stercoralis\u003c/em\u003e: three from sub-Saharan Africa, and six from Asia (Table 4). The prevalence of strongyloidiasis, defined as a positive serology and at least one positive fecal test, was 1.3% (95% CI: 0.6% - 2.5%).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eSimilarly, different assays were used for the screening of schistosomiasis, including serology for all forms of infection and diagnostics on stool and urine, targeting intestinal and urinary schistosomiasis, respectively (Table 5). Overall, 50 out of 388 participants was positive to at least one fecal or stool test, all from sub-Saharan Africa. Thus, the prevalence of schistosomiasis, defined as a positive serology and at least one positive fecal or urinary test, was 12.9% (95% CI: 9.7% - 16.6%).\u003c/p\u003e\n\u003cp\u003eFurther, 332 individuals from sub-Saharan Africa were tested with the pan-filaria serology. Twenty-three individuals out of the 332 (6.9%) were positive, so were tested for microfilaremia. The latter was positive in six (26.1%) out of the 23 serology-positive individuals, permitting the diagnosis of two \u003cem\u003eLoa loa\u003c/em\u003e and four \u003cem\u003eMansonella perstans\u0026nbsp;\u003c/em\u003ecases. The prevalence of filariasis, defined by a positive serology and the presence of microfilaremia, was 1.8% (95% CI: 0.7% - 3.9%).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eEosinophilia\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe median eosinophil count was 200/\u0026micro;L (IQR 100-300) in the whole cohort, including 21% subjects (n=141) with an eosinophil count \u0026ge;400/\u0026micro;L. Median eosinophil count in individuals from sub-Saharan Africa was 200 (IQR 100-300). For Asia, median eosinophil count was 200 (IQR 100-400). Median eosinophil count of people from North Africa was 100 (IQR 100-300).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAs for eosinophilia by geographical region of origin, it was present in 64 of 351 (18.2%) individuals from sub-Saharan Africa (median eosinophil count 600 (IQR: 500-900)), 64 of 238 (26.9%) individuals from Asia (median eosinophil count 500 (IQR 400-800)), 13 of 84 (15.5%) subjects from North Africa (median eosinophil count 500 (IQR: 400-600)).\u003c/p\u003e\n\u003cp\u003eThe multivariable model for sub-Saharan Africa found a significant association between eosinophilia and schistosomiasis (OR 4.31, 95%CI 2.10-8.84, p\u0026lt;0.001).\u003c/p\u003e\n\u003cp\u003eFor Asia, eosinophilia was significantly associated with strongyloidiasis (OR 8.11, 95%CI 1.44-82.6, p=0.017) and with hookworm (OR 29.5, 95%CI 3.26-3,891, p\u0026lt;0.001). As regards the sub-group of individuals from North Africa, models were not possible due to the extremely low frequency of parasitic infections diagnosed.\u0026nbsp;\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe first notable finding from our study is the significant shift in the geographical origin of migrants. The proportion of migrants from Asia has increased to 35.3%, compared to 21% in our previous study (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. This shift aligns with global migration trends and the most recent Italian estimates [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Such a change in the geographical origin of migrants should be considered when adapting guidelines and recommendations for screening both infectious and non-infectious diseases to the evolving epidemiological landscape.\u003c/p\u003e \u003cp\u003eIn this context, our study offers an updated overview of the prevalence of infectious diseases among recently arrived migrants in Italy, nine years after our previous work in the same setting [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. The findings further confirm the relevance of infectious diseases in this population, with significant differences observed based on migrants' geographical origin.\u003c/p\u003e \u003cp\u003eHIV prevalence among migrants in this study was relatively low, with an overall rate of 1.5%, which is comparable to the prevalence observed in our previous study (1.3%) [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Similarly, there was a notable geographic disparity, with the majority of cases being observed among migrants from sub-Saharan Africa (90%). This is consistent with ECDC estimates as well as previous studies showing the highest HIV prevalence rates in sub-Saharan Africa, highlighting the continued need for comprehensive HIV screening and awareness programs targeting individuals from that geographical area [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. The low prevalence observed among migrants from Asia and North Africa suggests that a targeted approach might be sufficient in those populations, rather than universal screening.\u003c/p\u003e \u003cp\u003eRegarding HBV infection, 6.1% of participants were positive for HBsAg. Of note, HBsAg positivity in our study was lower than both our previous work (i.e. 11.6%) and similar studies on migrant populations [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Additionally, 55.1% of individuals had negative HBV serology, indicating a substantial proportion of susceptible individuals who could benefit from vaccination programs. In particular, 75.9% of Asian migrants and 79.8% of North African migrants were eligible for HBV vaccination, emphasizing the need for tailored immunization strategies.\u003c/p\u003e \u003cp\u003eAlthough the overall prevalence of HCV in our cohort was low (0.8%), it remains noteworthy, particularly among individuals from sub-Saharan Africa and Asia. The prevalence observed in our study is lower than what has been reported in the literature but is consistent with our data from 2014\u0026ndash;2015 [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. However, this emphasizes the importance of ongoing surveillance, as even low prevalence rates can allow for early detection and intervention, preventing long-term complications such as liver cirrhosis and hepatocellular carcinoma.\u003c/p\u003e \u003cp\u003eSyphilis was detected in 2% of the migrants, which is consistent with findings from other studies that have addressed sexual health within migrant populations [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. The prevalence was particularly high among sub-Saharan African migrants (3.5%) and relatively low in migrants from Asia and North Africa. In our previous study, 4.5% of participants from sub-Saharan Africa and 1.0% of those from Asia tested positive. This emphasizes the need for continued vigilance in screening for sexually transmitted infections, particularly in populations with higher rates of sexual risk behaviors and prior exposure in endemic regions.\u003c/p\u003e \u003cp\u003eTuberculosis emerged as one of the most concerning findings in our study. The prevalence of TBI was 24.5%, while TB disease was diagnosed in 1.2% of participants, including both pulmonary and extrapulmonary forms. These results underscore the importance of comprehensive diagnostic strategies for TB among newly arrived migrants. The rate of TBI is consistent with epidemiological data from high-burden regions such as sub-Saharan Africa and Asia [\u003cspan additionalcitationids=\"CR15 CR16\" citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e], from which most of our cohort originated. These findings reinforce the need to maintain systematic TB screening upon arrival in Europe and to initiate preventive treatment for TBI, which is essential to reduce the risk of disease reactivation and subsequent transmission within host countries.\u003c/p\u003e \u003cp\u003eA particularly relevant aspect of our study concerns helminthic infections. We observed an overall proportion of 12.3% for at least one helminthic infection diagnosed through a positive stool test and/or urine test, with clear differences by geographical region.\u003c/p\u003e \u003cp\u003eThe prevalence of strongyloidiasis was 1.3%, which is consistent with the stool-based prevalence reported by Asundi et al. (1.8%) [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. Our study also highlights a significant seroprevalence of strongyloidiasis (7.2%), with seropositivity markedly higher among Asian migrants (13.6%). Notably, our findings are lower than the pooled seroprevalence of 12.2% reported by Asundi et al. [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. It should be noted that different serological assays have a wide range of sensitivity and specificity values, with most concerns relating the potential cross-reactivity with other nematodes [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. However, due to the potential development of severe or disseminated infection in cases of immunocompromise, treatment of individuals who are only positive for serology is considered justified. Therefore, in this setting, lower specificity is not regarded as problematic as lower sensitivity.\u003c/p\u003e \u003cp\u003eThe prevalence of schistosomiasis was 12.9%, with all cases, as expected, found among migrants from sub-Saharan Africa. It is worth noting that our findings are higher than the stool-based prevalence of 0.95% and the urine-based prevalence of 6.8% reported by Asundi et al. [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. Also, the seroprevalence for \u003cem\u003eSchistosoma\u003c/em\u003e spp. in our cohort was higher (52.6%) than that reported by Asundi et al. (18.4%), likely reflecting the low specificity of the test and the need for alternative diagnostic approaches for schistosomiasis, similarly to strongyloidiasis [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eFilariasis remains an underdiagnosed parasitic disease in migrant populations, with limited data available in non-endemic settings [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. Data on the prevalence of filariasis among migrants in Europe remain scarce, and most available epidemiological evidence comes from studies conducted in endemic regions of Africa [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. This knowledge gap complicates the development of targeted screening strategies in migrant populations, particularly given the clinical implications of filarial infections. Loiasis has recently been associated with increased mortality in cases with a high microfilarial burden, with eyeworm and Calabar swellings as characteristic clinical features; however, the disease can also present with atypical, non-specific symptoms [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. While infection with \u003cem\u003eM. perstans\u003c/em\u003e is generally considered less severe than other filarial infections, it can still lead to long-term symptoms and complications in certain individuals, such as abdominal pain and dermatitis [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Moreover, the stool tests for other parasitic diseases, including hookworm and \u003cem\u003eT. trichiura\u003c/em\u003e, revealed significant rates of infection, particularly among migrants from Asia.\u003c/p\u003e \u003cp\u003eThese findings confirm that routine screening for helminths is key a component of migrant health assessments, especially since these infections are often asymptomatic in the early stages but can lead to severe health consequences if untreated [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. The cost-effectiveness and ease of treatment for these parasitic infections further emphasize the importance of including them in national screening protocols for newly arrived migrants.\u003c/p\u003e \u003cp\u003eEosinophilia was present in 18.3% of the screened migrants and was significantly associated with helminthic infections. This association was especially pronounced among migrants from sub-Saharan Africa and Asia. Our analysis confirmed that \u003cem\u003eS. stercoralis\u003c/em\u003e and \u003cem\u003eSchistosoma\u003c/em\u003e spp. were the most frequently associated parasites, in line with previous studies [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. Specifically, eosinophilia was observed in 18.2% of African migrants and 26.9% of Asian migrants, with the condition predominantly linked to schistosomiasis in African migrants and strongyloidiasis in Asian migrants. The sensitivity of eosinophilia as a marker for helminthiasis is well recognized, but its specificity remains low, as it can be influenced by non-infectious conditions such as allergies and autoimmune diseases [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. Remarkably, our findings suggest that eosinophilia alone is insufficient to rule out helminthic infections. Among \u003cem\u003eS. stercoralis\u003c/em\u003e cases, 2/9 (22.2%) of infected individuals did not present eosinophilia, emphasizing the need for systematic screening. Similarly, 27/50 (54.0%) patients with \u003cem\u003eSchistosoma\u003c/em\u003e spp. infections did not have eosinophilia, suggesting that chronic infections may not always trigger a sustained eosinophilic response [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. These results highlight the importance of a combined diagnostic approach, integrating eosinophilia assessment with direct parasitological methods, serology, and molecular techniques to improve case detection.\u003c/p\u003e \u003cp\u003eOne of the main limitations of our study is its retrospective nature, which may have affected the quality of data collection. A comparison of prevalence with data from previous studies is challenging due to differences in the definitions of helminthic infections and the use of various diagnostic tests for screening (e.g., different serological assays for \u003cem\u003eS. stercoralis\u003c/em\u003e and \u003cem\u003eSchistosoma\u003c/em\u003e spp.). Additionally, the collinearity between eosinophilia and the presence of certain parasites posed a challenge in constructing robust multivariable models to assess risk factors, as reflected in the wide confidence intervals of the OR estimates.\u003c/p\u003e \u003cp\u003eFurthermore, our findings reflect the specific characteristics of the local migrant population, which may limit their applicability to other settings with different demographic and epidemiological profiles. Additionally, the distinction between asylum seekers and undocumented migrants was not addressed in the paper, and no analysis was performed to explore potential differences between these two categories.\u003c/p\u003e \u003cp\u003eFinally, with regard to TB classification, we did not distinguish between subclinical and symptomatic forms of TB [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e], as this distinction was beyond the scope and focus of the present study.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eOur findings support the need for a tailored approach to screening for infectious diseases in migrants, adapting strategies based on geographical origin. The integration of effective screening protocols and expanded access to vaccination and early treatment could significantly improve both individual and public health outcomes.\u003c/p\u003e \u003cp\u003eHelminthic infections, particularly \u003cem\u003eS. stercoralis\u003c/em\u003e and \u003cem\u003eSchistosoma\u003c/em\u003e spp., remain highly prevalent, and eosinophilia alone is not a sufficient screening tool. Systematic, evidence-based screening programs are essential to ensure early detection and treatment, reducing the burden of infectious diseases in migrant populations and preventing long-term complications.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003e\u003cem\u003eAcknowledgements\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe would like to thank the nurses, medical doctors, and laboratory staff at the DITM for their dedication to migrant care. We are also grateful to all the study participants.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eAuthor contribution\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTU:\u003c/strong\u003e Conceptualization, Methodology, Investigation, Data curation, Project administration, Visualization, Writing \u0026ndash; original draft, Writing \u0026ndash; review and editing. LB: Investigation, Data curation, Visualization, Writing \u0026ndash; review and editing. AZ: Investigation, Data curation, Writing \u0026ndash; review and editing. CM\u003cstrong\u003e:\u003c/strong\u003e Formal analysis, Writing \u0026ndash; original draft, Writing \u0026ndash; review and editing. \u003cstrong\u003ePC:\u003c/strong\u003e Investigation, Writing \u0026ndash; review and editing. ES: Investigation, Writing \u0026ndash; review and editing. LM\u003cstrong\u003e:\u003c/strong\u003e Investigation, Writing \u0026ndash; review and editing. FG: Conceptualization, Methodology, Supervision, Writing \u0026ndash; review and editing. DB\u003cstrong\u003e:\u003c/strong\u003e Conceptualization, Methodology, Supervision, Writing \u0026ndash; original draft, Writing \u0026ndash; review and editing.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eFunding\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was partly funded by the Italian Ministry of Health (Ricerca corrente Linea L3P1) with funds to IRCCS Sacro Cuore Don Calabria Hospital. The funding source had no role in study design, writing, and submission.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eAvailability of data and materials\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data underlying this article will be shared on reasonable request to the corresponding author.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eEthics approval\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study protocol received ethical clearance from the ethics committee for clinical trials in the province of Verona and Rovigo (Comitato Etico per la sperimentazione Clinica delle Province di Verona e Rovigo) on the 2\u003csup\u003end\u003c/sup\u003e of July 2024 (protocol number 29).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eCompeting interest\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.\u0026nbsp;\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eMcAuliffe M, Oucho LA, editors. 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The definition of tuberculosis infection based on the spectrum of tuberculosis disease. Breathe (Sheff). 2021;17:210079. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1183/20734735.0079-2021\u003c/span\u003e\u003cspan address=\"10.1183/20734735.0079-2021\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003e\u003cstrong\u003eTable 1.\u0026nbsp;\u003c/strong\u003eDemographic Characteristics of Study Participants\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"4\" valign=\"top\"\u003e\n \u003cp\u003eRegion\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eOverall\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eSub-Saharan Africa\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eAsia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eNorth Africa\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eN=674\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eN=352\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eN=238\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eN=84\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eMedian age in years (IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e25 (20-31)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e23 (19-29)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e27 (23-34)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e24 (18-32)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eMale, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e582 (86.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e284 (80.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e223 (93.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e75 (89.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eMedian number of months in country (IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e3 (1-5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2 (1-5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e3 (2-5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2 (1-6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2.\u0026nbsp;\u003c/strong\u003eTuberculosis screening results\u0026nbsp;\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd colspan=\"4\" valign=\"top\"\u003e\n \u003cp\u003eRegion\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003ep-value*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eOverall\u003cbr\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eSub-Saharan Africa\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eAsia\u003cbr\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eNorth Africa\u003cbr\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"6\" valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eNegative\u003c/p\u003e\n \u003cp\u003en (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e460 (70.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e207 (61.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e181 (78.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e72 (85.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eTBI\u003c/p\u003e\n \u003cp\u003en (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e160 (24.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e111 (32.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e43 (18.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e6 (7.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003ePreviously treated TB\u003c/p\u003e\n \u003cp\u003en (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e2 (0.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1 (0.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1 (1.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003ePTB\u003c/p\u003e\n \u003cp\u003en (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e5 (0.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e2 (0.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e3 (1.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eEPTB\u003c/p\u003e\n \u003cp\u003en (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e3 (0.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e2 (0.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1 (0.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eMissing\u003c/p\u003e\n \u003cp\u003en\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"6\" valign=\"top\"\u003e\n \u003cp\u003e\u003csup\u003e*\u003c/sup\u003e Fisher\u0026rsquo;s exact test\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eTBI: Tuberculosis infection; PTB: Pulmonary TB; EPTB: Extrapulmonary TB\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3.\u0026nbsp;\u003c/strong\u003eStool microscopy results\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"4\" valign=\"top\"\u003e\n \u003cp\u003eRegion\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eOverall\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eSub-Saharan Africa\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eAsia\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eNorth Africa\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eIndividuals screened by stool microscopy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e618\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e333\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e213\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e72\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003ePositive for\u0026nbsp;\u003cem\u003eS. stercoralis\u003c/em\u003e larvae\u003cbr\u003e\u0026nbsp;n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e3 (0.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1 (0.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e2 (0.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003ePositive for\u0026nbsp;\u003cem\u003eS. mansoni\u003c/em\u003e eggs\u003cbr\u003e\u0026nbsp;n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e28 (4.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e28 (8.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003ePositive for hookworm\u003csup\u003e1\u003c/sup\u003e eggs\u003cbr\u003e\u0026nbsp;n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e12 (1.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e6 (1.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e6 (2.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003ePositive for\u0026nbsp;\u003cem\u003eA. lumbricoides\u0026nbsp;\u003c/em\u003eeggs\u003cbr\u003e\u0026nbsp;n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1 (0.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1 (0.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003ePositive for\u0026nbsp;\u003cem\u003eT. trichiura\u003c/em\u003e eggs\u003cbr\u003e\u0026nbsp;n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e6 (1.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e6 (2.8%)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003ePositive for other parasites\u003csup\u003e2\u003c/sup\u003e\u003cbr\u003e\u0026nbsp;n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e244 (39.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e163 (48.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e57 (26.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e24 (33.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003csup\u003e1\u003c/sup\u003e Includes \u003cem\u003eAncylostoma duodenale\u003c/em\u003e and \u003cem\u003eNecator americanus\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e2\u0026nbsp;\u003c/sup\u003eReporting is focused on helminths determined to be clinically relevant, such as soil-transmitted helminths. Some other parasites, both helminths and protozoa, might not have a clinical relevance and are included in the other parasites group (e.g. \u003cem\u003eHymenolepis nana\u003c/em\u003e and \u003cem\u003eEndolimax nana\u003c/em\u003e).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 4.\u0026nbsp;\u003c/strong\u003e\u003cem\u003eStrongyloides stercoralis\u003c/em\u003e results\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"4\" valign=\"top\"\u003e\n \u003cp\u003eRegion\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003ep-value*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eOverall\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eSub-Saharan Africa\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eAsia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eNorth Africa\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eSerology\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eIndividuals screened by serology\u003c/p\u003e\n \u003cp\u003en\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e671\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e351\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e204\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e82\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eNegative\u003c/p\u003e\n \u003cp\u003en (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e623 (92.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e337 (96.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e204 (86.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e82 (97.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003ePositive\u003c/p\u003e\n \u003cp\u003en (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e48 (7.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e14 (4.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e32 (13.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e2 (2.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eStool PCR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eIndividuals screened by stool PCR\u003c/p\u003e\n \u003cp\u003en\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e142\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e57\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eNegative\u003c/p\u003e\n \u003cp\u003en (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e138 (97.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e65 (98.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e55 (96.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e18 (94.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003ePositive\u003c/p\u003e\n \u003cp\u003en (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e4 (2.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1 (1.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e2 (3.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1 (5.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eStool microscopy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eIndividuals screened by stool microscopy\u003c/p\u003e\n \u003cp\u003en\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e618\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e333\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e213\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eNegative\u003c/p\u003e\n \u003cp\u003en (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e615 (99.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e332 (99.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e211 (99.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e72 (100.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003ePositive\u003c/p\u003e\n \u003cp\u003en (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e3 (0.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1 (0.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e2 (0.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eAPC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026gt;0.9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eIndividuals screened by APC\u003c/p\u003e\n \u003cp\u003en\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eNegative\u003c/p\u003e\n \u003cp\u003en (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e21 (70.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e8 (72.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e12 (66.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1 (100.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003ePositive\u003c/p\u003e\n \u003cp\u003en (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e9 (30.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e3 (27.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e6 (33.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eMissing\u003c/p\u003e\n \u003cp\u003en\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e644\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e341\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e220\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e83\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"6\" valign=\"top\"\u003e\n \u003cp\u003e*Pearson\u0026rsquo;s Chi-squared test; Fisher\u0026rsquo;s exact test\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 5.\u0026nbsp;\u003c/strong\u003e\u003cem\u003eSchistosoma\u003c/em\u003e spp. results\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" class=\"fr-table-selection-hover\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"top\"\u003e\n \u003cp\u003eRegion\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003ep-value*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eOverall\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eSub-Saharan Africa\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eNorth Africa\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"3\" valign=\"top\"\u003e\n \u003cp\u003eSerology\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.084\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eIndividuals screened by serology\u003c/p\u003e\n \u003cp\u003en\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e386\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e350\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eNegative\u003c/p\u003e\n \u003cp\u003en (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e183 (47.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e161 (46.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e22 (61.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003ePositive\u003c/p\u003e\n \u003cp\u003en (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e203 (52.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e189 (54.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e14 (38.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\" valign=\"top\"\u003e\n \u003cp\u003eStool PCR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eIndividuals screened by stool PCR\u003c/p\u003e\n \u003cp\u003en\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eNegative\u003c/p\u003e\n \u003cp\u003en (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e69 (92.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e61 (92.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e8 (88.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003ePositive\u003c/p\u003e\n \u003cp\u003en (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e6 (8.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e5 (7.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1 (11.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"3\" valign=\"top\"\u003e\n \u003cp\u003eStool microscopy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eIndividuals screened by stool microscopy\u003c/p\u003e\n \u003cp\u003en\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e364\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e333\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eNegative\u003c/p\u003e\n \u003cp\u003en (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e336 (92.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e305 (91.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e31 (100.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003ePositive\u003c/p\u003e\n \u003cp\u003en (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e28 (7.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e28 (8.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"3\" valign=\"top\"\u003e\n \u003cp\u003eUrine PCR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eIndividuals screened by urine PCR\u003c/p\u003e\n \u003cp\u003en\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eNegative\u003c/p\u003e\n \u003cp\u003en (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e19 (100.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e19 (100.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003ePositive\u003c/p\u003e\n \u003cp\u003en (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eUrine microscopy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eIndividuals screened by urine microscopy\u003c/p\u003e\n \u003cp\u003en\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e355\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e322\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eNegative\u003c/p\u003e\n \u003cp\u003en (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e335 (94.4%)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e302 (93.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e33 (100.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003ePositive\u003c/p\u003e\n \u003cp\u003en (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e20 (5.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e20 (6.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eMissing\u003c/p\u003e\n \u003cp\u003en\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e81\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"5\" valign=\"top\"\u003e\n \u003cp\u003e*Pearson\u0026rsquo;s Chi-squared test; Fisher\u0026rsquo;s exact test\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"tropical-medicine-and-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"tmah","sideBox":"Learn more about [Tropical Medicine and Health](https://tropmedhealth.biomedcentral.com/)","snPcode":"41182","submissionUrl":"https://submission.springernature.com/new-submission/41182/3","title":"Tropical Medicine and Health","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Migrants, Screening, Tuberculosis, Helminths, Schistosomiasis, Strongyloidiasis","lastPublishedDoi":"10.21203/rs.3.rs-6930017/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6930017/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eMigration to Europe has increased in recent years, with Italy serving as a major entry point. Ensuring adequate healthcare for newly arrived migrants includes the prevention and management of infectious diseases. This study aimed to estimate the prevalence of selected infections among migrants in northern Italy.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eWe conducted a retrospective cross-sectional study at the Department of Infectious - Tropical Diseases and Microbiology (DITM) of the IRCCS Sacro Cuore Don Calabria Hospital, Negrar di Valpolicella (Verona, Italy) between January 2023 and May 2024. Asylum seekers and undocumented migrants aged\u0026thinsp;\u0026ge;\u0026thinsp;14 years who had arrived within the previous six months from Africa or Asia were screened for tuberculosis (TB), HIV, hepatitis B (HBV), hepatitis C (HCV), syphilis, strongyloidiasis, schistosomiasis, other intestinal helminthic infections, and filariasis. Diagnostic methods comprised serological, microscopic, molecular, and imaging techniques, applied as appropriate.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eAmong the 674 migrants screened (median age: 25 years; 86.4% male), TB infection was detected in 25.4%, and 2.9% were diagnosed with TB disease. HIV prevalence was 1.5%, primarily among individuals from sub-Saharan Africa. Chronic HBV infection was identified in 6.1% of participants, while 55.1% were seronegative and thus eligible for vaccination. Helminthic infections were found in 12.3%, mainly strongyloidiasis and schistosomiasis. Eosinophilia was present in 18.3% and was significantly associated with helminthic infections.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eThese findings underscore the persistent burden of infectious diseases among migrant populations and support the implementation of geographically tailored screening programs to improve early detection and public health outcomes.\u003c/p\u003e","manuscriptTitle":"Screening for infectious and neglected tropical diseases among newly arrived migrants from Africa and Asia: a retrospective study from Verona province, Italy","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-07-01 09:29:58","doi":"10.21203/rs.3.rs-6930017/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-07-22T13:07:31+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-07-22T12:46:25+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-07-15T08:29:30+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-07-14T10:12:27+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"166857591455870291736228252464323459562","date":"2025-07-12T06:03:05+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"18029790274917794247657348640979395687","date":"2025-07-11T16:29:31+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-07-11T06:52:17+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"113075217384464028458133206748710982104","date":"2025-06-30T07:02:06+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"152296066877530960108626522046441285629","date":"2025-06-26T04:35:01+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-06-26T04:20:29+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-06-25T23:32:30+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-06-25T23:31:06+00:00","index":"","fulltext":""},{"type":"submitted","content":"Tropical Medicine and Health","date":"2025-06-19T09:54:32+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"tropical-medicine-and-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"tmah","sideBox":"Learn more about [Tropical Medicine and Health](https://tropmedhealth.biomedcentral.com/)","snPcode":"41182","submissionUrl":"https://submission.springernature.com/new-submission/41182/3","title":"Tropical Medicine and Health","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"06eb2e8d-5e9e-4ada-9c8a-04614e5f8641","owner":[],"postedDate":"July 1st, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-09-01T16:01:22+00:00","versionOfRecord":{"articleIdentity":"rs-6930017","link":"https://doi.org/10.1186/s41182-025-00796-4","journal":{"identity":"tropical-medicine-and-health","isVorOnly":false,"title":"Tropical Medicine and Health"},"publishedOn":"2025-08-28 15:57:38","publishedOnDateReadable":"August 28th, 2025"},"versionCreatedAt":"2025-07-01 09:29:58","video":"","vorDoi":"10.1186/s41182-025-00796-4","vorDoiUrl":"https://doi.org/10.1186/s41182-025-00796-4","workflowStages":[]},"version":"v1","identity":"rs-6930017","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6930017","identity":"rs-6930017","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}