Crude Estimates Research Articles

Prognostic imaging variables for recurrent laryngeal and hypopharyngeal carcinoma treated with primary chemoradiotherapy: A systematic review and meta-analysis.

BackgroundIn this systematic review, we aim to identify prognostic imaging variables of recurrent laryngeal or hypopharyngeal carcinoma after chemoradiotherapy.MethodsA systematic search was performed in PubMed and EMBASE (1990–2020). The crude data and effect estimates were extracted for each imaging variable. The level of evidence of each variable was assessed and pooled risk ratios (RRs) were calculated.ResultsTwenty‐two articles were included in this review, 17 on computed tomography (CT) and 5 on magnetic resonance imaging (MRI) variables. We found strong evidence for the prognostic value of tumor volume at various cut‐off points (pooled RRs ranging from 2.09 to 3.03). Anterior commissure involvement (pooled RR 2.19), posterior commissure involvement (pooled RR 2.44), subglottic extension (pooled RR 2.25), and arytenoid cartilage extension (pooled RR 2.10) were also strong prognostic factors.ConclusionPretreatment tumor volume and involvement of several subsites are prognostic factors for recurrent laryngeal or hypopharyngeal carcinoma after chemoradiotherapy.

Prevalence and Factors Associated with Diabetes among Bangladeshi Adults: An Analysis of Demographic and Health Survey 2017–18

BackgroundThe burden of diabetes is increasing in most developing countries, including Bangladesh. However, there is no recent research into the prevalence and factors associated with this condition in this country. This study intended to fill this gap. MethodsThis cross-sectional study analyzed Bangladesh Demographic and Health Survey 2017–18 data. After crude and age-adjusted prevalence estimation, multilevel logistic regression analyses were employed. ResultsAmong 12,298 participants (mean age: 40 years, 57% females), the crude and age-adjusted prevalence of diabetes was 9.9% and 9.7%, respectively. The crude prevalence was 9.5% among females and 10.5% among males. The age-adjusted prevalence was 9.8% among females and 9.5% among males. The adjusted odds (adjusted odds ratio, 95% confidence interval) of diabetes was higher among 30–39 (2.1, 1.7–2.6), 40–49 (3.3, 2.7–4.1), 50–59 (4.9, 3.9–6.2), 60–69 (5.1, 4.0–6.5), and ≥70-year-olds (5.0, 3.7–6.6) than 18–29-year-olds; 25–29.9 (1.6, 1.4–1.9) and 30 (1.9, 1.5–2.5) kg/m2 body mass index (BMI) than those with BMI <25 kg/m2; primary or above (1.2, 1.0–1.5) education level than those without formal education; middle (1.3, 1.0–1.7), richer (1.7, 1.3,2.2), or richest (2.6, 2.0–3.3) wealth quintiles than those with poorest wealth quintile. Division of residence was also significantly associated. ConclusionThis study found that people with older age, overweight/obesity, higher socioeconomic status, and residence in some administrative divisions had higher prevalence and odds of diabetes. To reduce the prevalence of diabetes in Bangladesh, future efforts should aim to address these factors with adequate prevention and control programs.

Assessment of Aerodynamic Roughness Length Using Remotely Sensed Land Cover Features and MODIS

Wind speed profile has a significant role in environmental transport phenomena whereby Roughness length is a governing factor that determines wind speed profile. Normally, relatively crude estimates of roughness length are used in global climate models based on constant values for each specific land cover category. However, a significant variation may exist within any one of these land cover categories. For this reason, it is necessary to derive detailed roughness length distribution over areas under consideration. Satellite observations can be used to assess the details of roughness length distribution. The aim of the present study was to develop method for roughness length assessment based on remotely sensed Normalized Difference Vegetation Index (NDVI) and landscape images for the entire Iraq area. The NDVI was generated using MODIS data (MOD13Q1) at 250 m resolution acquired on 23th April 2015 for whole Iraq. And the landscape images were classified based on land use and land cover (LU/LC) that relates general classes of LU/LC and values of roughness length coefficient. Taking into consideration a specific range of NDVI values of each landscape category, a correlation analysis was used to determine the aerodynamic roughness between the values of (NDVI) and the aerodynamic roughness based on the European Wind Atlas classification and the Royal Netherlands Meteorological Institute. A quantitative relationship was set up to retrieve the aerodynamic roughness length from MODIS data (MOD13Q1) where R2 = 0.96. Experiments prove that the proposed methodology can provide accurate roughness length estimations for the spatial and temporal analysis of land surface. The findings of this study will enhance sustainability in Iraq and many other regions of the world, thus, supporting the Sustainable Development Goals (SDGs) through the establishment of wind farms especially in countries with coastal areas that can serve as a major source of the national electricity.

Optimizing Adaptive Neuro Fuzzy Inference System (ANFIS) parameters using Cuckoo Search (Case study of world crude oil price estimation)

There are some methods that have found for estimating data and one of them is Adaptive Neuro Fuzzy Inference System (ANFIS). In estimation using ANFIS, there are some initial parameters such as premise parameters (nonlinear) and consequent parameters (linear) which should be fixed to be trained forward and backward by gradient descent. In this research with case study of world crude oil price estimation, initial ANFIS parameters will be optimized by Cuckoo Search method. Cuckoo Search uses reproduction strategy i.e. laying their eggs in the other bird’s nest. When the eggs are hatched, their chicks are fed by other birds. In Cuckoo Search method, initial ANFIS parameters is represented as bird nest position. Based on simulation, Cuckoo Search method can optimize initial ANFIS parameters giving the best estimation both of training data and testing data in world crude oil price estimation.

ES12.02 Defining High Risk

ES12.02 Defining High Risk

Propensity score matching for multilevel spatial data: accounting for geographic confounding in health disparity studies

BackgroundDiabetes is a public health burden that disproportionately affects military veterans and racial minorities. Studies of racial disparities are inherently observational, and thus may require the use of methods such as Propensity Score Analysis (PSA). While traditional PSA accounts for patient-level factors, this may not be sufficient when patients are clustered at the geographic level and thus important confounders, whether observed or unobserved, vary by geographic location.MethodsWe employ a spatial propensity score matching method to account for “geographic confounding”, which occurs when the confounding factors, whether observed or unobserved, vary by geographic region. We augment the propensity score and outcome models with spatial random effects, which are assigned scaled Besag-York-Mollié priors to address spatial clustering and improve inferences by borrowing information across neighboring geographic regions. We apply this approach to a study exploring racial disparities in diabetes specialty care between non-Hispanic black and non-Hispanic white veterans. We construct multiple global estimates of the risk difference in diabetes care: a crude unadjusted estimate, an estimate based solely on patient-level matching, and an estimate that incorporates both patient and spatial information.ResultsIn simulation we show that in the presence of an unmeasured geographic confounder, ignoring spatial heterogeneity results in increased relative bias and mean squared error, whereas incorporating spatial random effects improves inferences. In our study of racial disparities in diabetes specialty care, the crude unadjusted estimate suggests that specialty care is more prevalent among non-Hispanic blacks, while patient-level matching indicates that it is less prevalent. Hierarchical spatial matching supports the latter conclusion, with a further increase in the magnitude of the disparity.ConclusionsThese results highlight the importance of accounting for spatial heterogeneity in propensity score analysis, and suggest the need for clinical care and management strategies that are culturally sensitive and racially inclusive.

Chinese clinical practice guidelines for perioperative blood glucose management.

With the increased incidence of diabetes, the number of diabetic patients who require surgical treatment is also increasing. Unfortunately, practices in this area lack standardisation. The purpose of this multidisciplinary, evidence-based guidelines for perioperative blood glucose management is to provide a comprehensive set of recommendations for clinicians treating diabetes with different types of surgery. The intended audience comprises Chinese endocrinologists, surgeons, anaesthetists, clinical pharmacists, nurses and professionals involved in perioperative blood glucose management. The guidelines were formulated as follows. First, a multidisciplinary expert group was established to identify and formulate key research questions on topics of priority according to the Population, Intervention, Comparator and Outcomes (PICO) process. We conducted a meta-analysis of available studies using Review Manager version 5.3, as appropriate. We pooled crude estimates as odds ratios with 95% confidence intervals using a random-effects model, and used the Grading of Recommendations Assessment, Development, and Evaluation methods to assess the quality of the retrieved evidence. Finally, 32 recommendations were gathered that covered 11 fields-management and coordination, endocrinologists' consultation, diabetes diagnosis, surgery timing and anaesthesia method, blood glucose target values and monitoring frequency, hypoglycaemia treatment, oral administration of blood glucose lowering drugs, use of insulin, enteral and parenteral nutritional, postoperative treatment and medication and education and training. Twenty-five systematic reviews and meta-analyses were conducted for these guidelines to address the PICO questions. These guidelines are intended to improve perioperative blood glucose management and help doctors in specifying medical diagnosis and treatment, and will be implemented / disseminated extensively in China.

Assessing the Impact on Health of Pharmacovigilance Activities: Example of Four Safety Signals

The impact of pharmacovigilance activities on public health remains under-investigated, and measuring the impact on health of pharmacovigilance activities for a specific safety signal is challenging. To gain more insight into the methodological challenges and the data required, we assessed the impact of pharmacovigilance on public health for four identified product-specific safety signals using publicly available data in the Netherlands. The assessment was on the impact of the intertwined and complementary steps of the pharmacovigilance pathways. The impact of pharmacovigilance on public health was assessed using the assessment support tool and 'open data' from the Netherlands for four different types of pharmacovigilance safety signals: (1) off-label use of cyproterone acetate/ethinyloestradiol (CPA/EE) and thrombotic risk after pharmacovigilance measures after 2014; (2) pergolide and the risk of cardiac valvulopathy after pharmacovigilance activities in 2003; (3) proton pump inhibitors and the risk of hypomagnesaemia after pharmacovigilance activities in 2011; (4) rosiglitazone withdrawal from the market because of cardiovascular effects in 2010. For the signals on CPA/EE and pergolide, a crude estimation of the impact could be made with varying degrees of assumptions based on the risk described in the literature and utilisation data. This article highlights the methodological challenges and the data required to assess the impact of product-specific safety signals. A structured assessment support tool can be used as a guide for the necessary data elements and steps needed for the measurement or estimation of impact of pharmacovigilance activities on public health, provided that the appropriate data are available.

Sample Size Estimation in Veterinary Epidemiologic Research.

In the design of intervention and observational epidemiological studies sample size calculations are used to provide estimates of the minimum number of observations that need to be made to ensure that the stated objectives of a study are met. Justification of the number of subjects enrolled into a study and details of the assumptions and methodologies used to derive sample size estimates are now a mandatory component of grant application processes by funding agencies. Studies with insufficient numbers of study subjects run the risk of failing to identify differences among treatment or exposure groups when differences do, in fact, exist. Selection of a number of study subjects greater than that actually required results in a wastage of time and resources. In contrast to human epidemiological research, individual study subjects in a veterinary setting are almost always aggregated into hierarchical groups and, for this reason, sample size estimates calculated using formulae that assume data independence are not appropriate. This paper provides an overview of the reasons researchers might need to calculate an appropriate sample size in veterinary epidemiology and a summary of sample size calculation methods. Two approaches are presented for dealing with lack of data independence when calculating sample sizes: (1) inflation of crude sample size estimates using a design effect; and (2) simulation-based methods. The advantage of simulation methods is that appropriate sample sizes can be estimated for complex study designs for which formula-based methods are not available. A description of the methodological approach for simulation is described and a worked example provided.

Displaying survival of patient groups defined by covariate paths: Extensions of the Kaplan-Meier estimator.

Extensions of the Kaplan-Meier estimator have been developed to illustrate the relationship between a time-varying covariate of interest and survival. In particular, Snapinn et al and Xu et al developed estimators to display survival for patients who always have a certain value of a time-varying covariate. These estimators properly handle time-varying covariates, but their clinical interpretation is limited. It is of greater clinical interest to display survival for patients whose covariates lie along certain defined paths. In this article, we propose extensions of Snapinn et al and Xu et al's estimators, providing crude and covariate-adjusted estimates of the survival function for patients defined by covariate paths. We also derive analytical variance estimators. We demonstrate the utility of these estimators with medical examples and a simulation study.

Central nervous system inflammatory demyelinating diseases and neuroimmunology in Singapore—Epidemiology and evolution of an emerging subspecialty

AbstractThe clinico‐pathologic entity of central nervous system inflammatory demyelinating diseases (CNS IDD) such as multiple sclerosis (MS) and neuromyelitis optica spectrum disorders (NMOSD) was recognized in Singapore as early as the 1960s but were previously under‐diagnosed and under‐researched. Access to neuroimmunology expertise, advanced neuroimaging and novel neural antibody biomarkers that distinguish aquaporin‐4 antibody‐positive NMOSD (AQP4 NMOSD) and myelin oligodendrocyte glycoprotein antibody disease (MOGAD) from MS have revolutionized the clinical management of patients with CNS IDD in Singapore. Based on pooled cross‐sectional data from government‐funded hospitals in 2020, we identified 468 CNS IDD patients (265 MS, 152 AQP4 NMOSD, and 51 MOGAD) in Singapore. Based on a population size of approximately 4 million, the crude prevalence estimates of MS are 6.6 per 100 000, AQP4 NMOSD 3.8 per 100 000, and MOGAD 1.3 per 100 000. There are marked differences in MS and AQP4 NMOSD prevalence between ethnic groups; MS prevalence is highest in Eurasian (mixed Caucasian‐Asian ancestry) (23.9 per 100 000), followed by Indian (17.5 per 100 000), Malay (9.2 per 100 000), and Chinese (4 per 100 000); AQP4 NMOSD prevalence is highest in Chinese (4.5 per 100 000), followed by Eurasian (3.9 per 100 000), Malay (1.5 per 100 000), and Indian (1.1 per 100 000). The past decade has seen remarkable growth in neuroimmunology in Singapore. We aim to foster the development of interdisciplinary care, clinical, translational, and health services research that impact local healthcare policies and research priorities, and patient support groups to better navigate through this rapidly evolving landscape.

Case fatality risk estimated from routinely collected disease surveillance data: application to COVID–19

Case fatality risk (CFR) is the probability of death among cases of a disease. A crude CFR estimate is the ratio of the number deaths to the number of cases of the disease. This estimate is biased, however, particularly during outbreaks of emerging infectious diseases such as COVID-19, because the death time of recent cases is subject to right censoring. Instead, we propose deconvolution methods applied to routinely collected surveillance data of unlinked case and death counts over time. We begin by considering the death series to be the convolution of the case series and the fatality distribution, which is the subdistribution of the time between diagnosis and death. We then use deconvolution methods to estimate this fatality distribution. This provides a CFR estimate together with information about the distribution of time to death. Importantly, this information is extracted without the need to make strong assumptions used in previous analyses. The methods are applied to COVID-19 surveillance data from a range of countries illustrating substantial CFR differences. Simulations show that crude approaches lead to underestimation, particularly early in an outbreak, and that the proposed approach can rectify this bias. An R package called covidSurv is available for implementing the analyses.

Is there an association between drug use and oral health conditions?

Data sources Databases searched included PsycINFO, PubMed, SciELO, Scopus and Web of Science.Study selection Cross-sectional, longitudinal and retrospective studies that compared caries, periodontal disease or tooth loss in people who use drugs as compared to those who do not. Studies that included psychiatric populations and alcohol or tobacco users were not included in the review. Qualitative studies, in vitro investigations, animal studies, reviews, case reports and series, letters to editor and conference abstracts were also excluded. The authors included only English studies published before 1 July 2019. Two independent reviewers screened the papers on title and abstract and then full text. In case of disagreements, these were discussed between the two reviewers and a third one was consulted if needed.Data extraction and synthesis Two reviewers extracted the data and contacted the primary authors for necessary clarifications, if needed. The unweighted kappa was applied to examine inter-examiner agreement. The Joanna Briggs Institute Critical Appraisal Checklist for observational studies was used to critically appraise the studies. The study selection results were presented through a flowchart. For the meta-analysis, the authors considered adjusted data. In some cases, crude estimates were used. Heterogeneity was estimated using the I2 statistic. The 'meta' package was used for the meta-analysis.Results Ten studies were included in the meta-analysis. Drug use was associated with higher risk of periodontal disease (OR 1.44; 95% CI 0.8-2.6) and higher DMFT index (OR 4.11; 95% CI 2.07-8.15).Conclusions The review showed high risk of periodontal disease and caries among people who use drugs. The authors concluded that this association may be explained by irregular tooth brushing and long history of drug use. It is important to develop programmes that aim to improve oral hygiene practices among people who use drugs.

SARS-CoV-2 Seroprevalence in Lithuania: Results of National Population Survey.

Summary. Background.Betacoronavirus SARS-CoV-2 has spread in early 2020 worldwide just in several months. The official statistics are consistently collected, but this is mainly based on symptomatic reports. This study was aimed to estimate the seroprevalence of SARS-CoV-2 infection in Lithuanian population.Materials and methods.Study was conducted during August–September 2020 in 6 municipalities of Lithuania. The sample comprised 3087 adult participants from the general population (mean age 53.7 years, 64% female). SARS-CoV-2 antibodies were assessed using AMP IgM/IgG Rapid Test, other data were based on self-report. Seroprevalence was assessed as a crude estimate and as adjusted by sensitivity-specificity of the test.Results.The crude seroprevalence in the total sample was 1.9%, the adjusted – 1.4%, ranging from 0.8% to 2.4% across municipalities. Among seroprevalent cases, 67.2% had IgG, 29.3% had IgM, and 3.5% had both IgG and IgM. An increased risk for seropositive test was observed among people who reported having had close contacts with SARS-CoV-2 positives (OR=5.49, p<0.001). At the borderline significance were female gender (OR=1.75, p=0.082) and non-smoking status (OR=2.95, p=0.072). Among the seropositive participants, 69.0% reported having had no COVID-19 symptoms since 1 March 2020, while 31.0% reported having had at least one of the symptoms.Conclusions.The SARS-CoV-2 seroprevalence in Lithuanian sample in August–September 2020 was 1.4%, ranging from 0.8% to 2.4% across municipalities. Given the overall official data, by the end of study (11 September 2020) the total COVID-19 rate in Lithuania was 117.5 per 100,000 population or 0.12%. This suggests more than 10 times higher prevalence of virus across the population than the official estimates.

The impact of volcanic emission of halogenated compounds on the Southern Hemisphere and Antarctic environment

The study aims to estimate and compare the global emission for 20 halocarbons from volcanic and hydrothermal sources into the Earth’s atmosphere. It follows from the results that the contribution of volcanic emission for these species in the depletion of stratospheric ozone in the catalytic halogen cycles does not exceed 0.1%. Still, they significantly impair the level of tropospheric ozone near the volcanoes. The scheme of gas-phase free radical chain halogenation of the hydrocarbons is proposed and confirmed by thermodynamic and kinetic calculations. This explains the experimental ratios between concentrations of CH3I : CH3Br : CH3Cl and CCl4 : CHCl3 : CH2Cl2 : CH3Cl in the volcanic gases. The possible volcanic emission of halocarbons from Erebus and explosive eruptions in the Southern Hemisphere during the Holocene do not have a notable impact on their content in the Antarctic ice. However, volcanic emission of hydrogen halides (HX, X = Cl, Br or I) from powerful eruptions in the Southern Hemisphere during Holocene could deplete the stratospheric ozone substantially, causing a drastic impact of the harmful UV-B radiation on the biota of continents and ocean. We calculated the injected Equivalent Effective Stratospheric Chlorine values and estimated the column ozone percentage change, Δ%O3, for 20 known volcano eruptions in the tropical belt and Southern latitudes. The estimates lead to more than 50% depletion of stratospheric ozone after past powerful volcanic eruptions. The range is estimated for possible ozone depletion after the eruption of Deception Island’s volcano occurred near 4000 BP (from 44 to 56%), which is comparable with those from Krakatoa, Samalas, and Tambora eruptions. A similar analysis was carried out for 192 yrs series of Mt Takahe (West Antarctica) halogen-rich volcanic eruptions at 17,7 kyr, showing extensive stratospheric ozone depletion over Antarctica. Crude estimations of stratospheric ozone depletion (Δ%O3) after Ferrar Large Igneous Province eruptions (183 Ma) in Antarctica were performed, considering the whole LIP volume of basaltic lavas, and they range from 49 to 83%. Given the very low emission rate of HCl due to non-eruptive degassing of the Mt. Erebus volcano, the volcanic emission of Erebus could not be a fundamental reason for modern springtime ozone hole formation over Antarctica.

Time evolution of many-body localized systems in two spatial dimensions

Many-body localization is a striking mechanism that prevents interacting quantum systems from thermalizing. The absence of thermalization behaviour manifests itself, for example, in a remanence of local particle number configurations, a quantity that is robust over a parameter range. Local particle numbers are directly accessible in programmable quantum simulators, in systems of cold atoms even in two spatial dimensions. Yet, the classical simulation aimed at building trust in quantum simulations is highly challenging. In this work, we present a comprehensive tensor network simulation of a many-body localized systems in two spatial dimensions using a variant of an iPEPS algorithm. The required translational invariance can be restored by implementing the disorder into an auxiliary spin system, providing an exact disorder average under dynamics. We can quantitatively assess signatures of many-body localization for the infinite system: Our methods are powerful enough to provide crude dynamical estimates for the transition between localized and ergodic phases. Interestingly, in this setting of finitely many disorder values, which we also compare with simulations involving non-interacting fermions and for which we discuss the emergent physics, localization emerges in the interacting regime, for which we provide an intuitive argument, while Anderson localization is absent.

Radiation Mapping for an Unmanned Aerial Vehicle: Development and Simulated Testing of Algorithms for Source Mapping and Navigation Path Generation.

Image reconstruction algorithms were developed for radiation source mapping and used for generating the search path of a moving radiation detector, such as one onboard an unmanned aerial vehicle. Simulations consisted of first assuming radioactive sources of varying complexity and estimating the radiation fields that would then be produced by that source distribution. Next, the "measurements" that would result from a pair of adjacent spatial locations were computed. A crude estimate of the source distribution likely to have produced such "measurements" was reconstructed based upon the limited measurements. Location of the next "measurement" was then determined as halfway between the location of the estimated source and the current "measurement." With each additional sample, improved source distribution reconstructions were made and used to inform the immediate direction of detector motion. Source reconstruction or mapping was formulated as an inverse problem solved with either maximum a posteriori or least squares (LS) regression deconvolution methods. Different amounts of noise were added to the simulated "measurements," allowing evaluation of the methods' performances as functions of signal-to-noise ratio of the measured map. As expected, methods that promote sparsity were better suited in reconstructing point sources. Reliable prior information of the source distribution also improved the reconstruction results, especially with distributed sources. With a non-negative least square algorithm and the suggested paths it generated, location of sources was successfully estimated to an accuracy of 0.014 m within nine iterations in a single-source scenario and 12 iterations in a two-source scenario, given a 10% error on the integrated counts and a Poisson distribution of the noise associated with the measured counts.

Renin--angiotensin system blockers and the risk of critical or fatal coronavirus disease 2019 in African Americans.

Renin--angiotensin system blockers and the risk of critical or fatal coronavirus disease 2019 in African Americans.

Pilot Study of Trans-oral Robotic-Assisted Needle Direct Tracheostomy Puncture in Patients Requiring Prolonged Mechanical Ventilation.

COVID-19 can induce severe respiratory problems that need prolonged mechanical ventilation in the intensive care unit. While Open Tracheostomy (OT) is the preferred technique due to the excellent visualization of the surgical field and structures, Percutaneous Tracheostomy (PT) has proven to be a feasible minimally invasive alternative. However, PT's limitation relates to the inability to precisely enter the cervical trachea at the exact spot since the puncture is often performed based on crude estimation from anatomical laryngeal surface landmarks. Besides, there is no absolute control of the trajectory and force required to make the percutaneous puncture into the trachea, resulting in inadvertent injury to the cricoid ring, cervical esophagus, and vessels in the neck. Therefore, we hypothesize that a flexible mini-robotic system, incorporating the robotic needling technology, can overcome these challenges by allowing the trans-oral robotic instrument of the cervical trachea. This approach promises to improve current PT technology by making the initial trachea puncture from an “inside-out” approach, rather than an “outside-in” manner, fraught with several technical uncertainties.

Zoonotic risk of Hansen's disease from community contact with wild armadillos: A systematic review and meta-analysis.

Understanding and quantifying the risk of Hansen's disease (HD) through zoonotic transmission of Mycobacterium leprae infection from wild armadillos is important because hunting, handling and consumption of these animals is widespread in communities where HD is endemic, posing a potential threat to the health of individuals and to HD elimination. We conducted a systematic review (PROSPERO CRD42019159891) of publications in MEDLINE, EMBASE, Global Health, Scopus, LILACS, Biblioteca Digital Brasileira de Teses e Dissertações, Catálogo de Teses e Dissertações de CAPES, and Biblioteca Virtual em Saúde up to 09/05/2020 using Mesh and text terms in English, Portuguese, Spanish and French. Random effects meta-analyses were performed including of subgroups by endemicity and type of exposure. Seven of the nine included studies were case-control, four from Brazil and three from the USA, comprising 1,124 cases and 2,023 controls in total. The other two studies, one from Brazil and one from Colombia, were cross-sectional. The overall summary estimate (odds ratio, OR) for the relative odds of HD comparing people who had direct contact with armadillos and/or had eaten armadillo meat with those who had not was OR=2.60 (95% CI 1.78-3.80, p<.001) with a predictive interval of OR=1.10-6.17. Summary odds ratios for specific exposures were as follows: indirect contact, OR=1.39 (95% CI 1.02, 1.89) (p=.04); eating, OR=2.29 (95% CI 1.13, 4.66) (p=.02); hunting, OR=2.54 (95% CI 1.21, 5.33) (p=.01). Most of the included studies had moderate risk of bias. Crude estimates were reduced by up to 24% when adjusted for confounders (where reported). Direct contact with wild armadillos was strongly associated with an increased risk of HD, whilst evidence for an increased risk of HD from indirect contact was weaker. The fraction of HD in endemic countries attributable to zoonotic transmission from armadillos remains unknown, but the precautionary principle needs to be adopted to protect public health.