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Scherbakov D, Mollalo A, Lenert L. Stressful life events in electronic health records: a scoping review. J Am Med Inform Assoc 2024:ocae023. [PMID: 38349862 DOI: 10.1093/jamia/ocae023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2023] [Revised: 01/19/2024] [Accepted: 01/27/2024] [Indexed: 02/15/2024] Open
Abstract
OBJECTIVES Stressful life events, such as going through divorce, can have an important impact on human health. However, there are challenges in capturing these events in electronic health records (EHR). We conducted a scoping review aimed to answer 2 major questions: how stressful life events are documented in EHR and how they are utilized in research and clinical care. MATERIALS AND METHODS Three online databases (EBSCOhost platform, PubMed, and Scopus) were searched to identify papers that included information on stressful life events in EHR; paper titles and abstracts were reviewed for relevance by 2 independent reviewers. RESULTS Five hundred fifty-seven unique papers were retrieved, and of these 70 were eligible for data extraction. Most articles (n = 36, 51.4%) were focused on the statistical association between one or several stressful life events and health outcomes, followed by clinical utility (n = 15, 21.4%), extraction of events from free-text notes (n = 12, 17.1%), discussing privacy and other issues of storing life events (n = 5, 7.1%), and new EHR features related to life events (n = 4, 5.7%). The most frequently mentioned stressful life events in the publications were child abuse/neglect, arrest/legal issues, and divorce/relationship breakup. Almost half of the papers (n = 7, 46.7%) that analyzed clinical utility of stressful events were focused on decision support systems for child abuse, while others (n = 7, 46.7%) were discussing interventions related to social determinants of health in general. DISCUSSION AND CONCLUSIONS Few citations are available on the prevalence and use of stressful life events in EHR reflecting challenges in screening and storing of stressful life events.
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Affiliation(s)
- Dmitry Scherbakov
- Biomedical Informatics Center, Medical University of South Carolina, Charleston, SC 29403, United States
| | - Abolfazl Mollalo
- Biomedical Informatics Center, Medical University of South Carolina, Charleston, SC 29403, United States
| | - Leslie Lenert
- Biomedical Informatics Center, Medical University of South Carolina, Charleston, SC 29403, United States
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Mollalo A, Hamidi B, Lenert L, Alekseyenko AV. Application of Spatial Analysis for Electronic Health Records: Characterizing Patient Phenotypes and Emerging Trends. Res Sq 2024:rs.3.rs-3443865. [PMID: 37886509 PMCID: PMC10602163 DOI: 10.21203/rs.3.rs-3443865/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/28/2023]
Abstract
Background Electronic health records (EHR) commonly contain patient addresses that provide valuable data for geocoding and spatial analysis, enabling more comprehensive descriptions of individual patients for clinical purposes. Despite the widespread use of EHR in clinical decision support and interventions, no systematic review has examined the extent to which spatial analysis is used to characterize patient phenotypes. Objective This study reviews advanced spatial analyses that employed individual-level health data from EHR within the US to characterize patient phenotypes. Methods We systematically evaluated English-language peer-reviewed articles from PubMed/MEDLINE, Scopus, Web of Science, and Google Scholar databases from inception to August 20, 2023, without imposing constraints on time, study design, or specific health domains. Results Only 49 articles met the eligibility criteria. These articles utilized diverse spatial methods, with a predominant focus on clustering techniques, while spatiotemporal analysis (frequentist and Bayesian) and modeling were relatively underexplored. A noteworthy surge (n = 42, 85.7%) in publications was observed post-2017. The publications investigated a variety of adult and pediatric clinical areas, including infectious disease, endocrinology, and cardiology, using phenotypes defined over a range of data domains, such as demographics, diagnoses, and visits. The primary health outcomes investigated were asthma, hypertension, and diabetes. Notably, patient phenotypes involving genomics, imaging, and notes were rarely utilized. Conclusions This review underscores the growing interest in spatial analysis of EHR-derived data and highlights knowledge gaps in clinical health, phenotype domains, and spatial methodologies. Additionally, this review proposes guidelines for harnessing the potential of spatial analysis to enhance the context of individual patients for future clinical decision support.
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Scherbakov D, Mollalo A, Lenert L. Stressful life events in electronic health records: a scoping review. Res Sq 2023:rs.3.rs-3458708. [PMID: 37886439 PMCID: PMC10602151 DOI: 10.21203/rs.3.rs-3458708/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/28/2023]
Abstract
Objective Stressful life events, such as going through divorce, can have an important impact on human health. However, there are challenges in capturing these events in electronic health records (EHR). We conducted a scoping review aimed to answer two major questions: how stressful life events are documented in EHR and how they are utilized in research and clinical care. Materials and Methods Three online databases (EBSCOhost platform, PubMed, and Scopus) were searched to identify papers that included information on stressful life events in EHR; paper titles and abstracts were reviewed for relevance by two independent reviewers. Results 557 unique papers were retrieved, and of these 70 were eligible for data extraction. Most articles (n=36, 51.4%) were focused on the statistical association between one or several stressful life events and health outcomes, followed by clinical utility (n=15, 21.4%), extraction of events from free-text notes (n=12, 17.1%), discussing privacy and other issues of storing life events (n=5, 7.1%), and new EHR features related to life events (n=4, 5.7%). The most frequently mentioned stressful life events in the publications were child abuse/neglect, arrest/legal issues, and divorce/relationship breakup. Almost half of the papers (n=7, 46.7%) that analyzed clinical utility of stressful events were focused on decision support systems for child abuse, while others (n=7, 46.7%) were discussing interventions related to social determinants of health in general. Discussion and Conclusions Few citations are available on the prevalence and use of stressful life events in EHR reflecting challenges in screening and storing of stressful life events.
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Affiliation(s)
- Dmitry Scherbakov
- Biomedical Informatics Center, Department of Public Health Sciences, Medical University of South Carolina
| | - Abolfazl Mollalo
- Biomedical Informatics Center, Department of Public Health Sciences, Medical University of South Carolina
| | - Leslie Lenert
- Biomedical Informatics Center, Department of Public Health Sciences, Medical University of South Carolina
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Scherbakov D, Mollalo A, Lenert L. Stressful life events in electronic health records: a scoping review. Res Sq 2023:rs.3.rs-3458708. [PMID: 37886439 PMCID: PMC10602151 DOI: 10.21203/rs.3.rs-3458708/v2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 02/27/2024]
Abstract
Objective Stressful life events, such as going through divorce, can have an important impact on human health. However, there are challenges in capturing these events in electronic health records (EHR). We conducted a scoping review aimed to answer two major questions: how stressful life events are documented in EHR and how they are utilized in research and clinical care. Materials and Methods Three online databases (EBSCOhost platform, PubMed, and Scopus) were searched to identify papers that included information on stressful life events in EHR; paper titles and abstracts were reviewed for relevance by two independent reviewers. Results 557 unique papers were retrieved, and of these 70 were eligible for data extraction. Most articles (n=36, 51.4%) were focused on the statistical association between one or several stressful life events and health outcomes, followed by clinical utility (n=15, 21.4%), extraction of events from free-text notes (n=12, 17.1%), discussing privacy and other issues of storing life events (n=5, 7.1%), and new EHR features related to life events (n=4, 5.7%). The most frequently mentioned stressful life events in the publications were child abuse/neglect, arrest/legal issues, and divorce/relationship breakup. Almost half of the papers (n=7, 46.7%) that analyzed clinical utility of stressful events were focused on decision support systems for child abuse, while others (n=7, 46.7%) were discussing interventions related to social determinants of health in general. Discussion and Conclusions Few citations are available on the prevalence and use of stressful life events in EHR reflecting challenges in screening and storing of stressful life events.
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Affiliation(s)
- Dmitry Scherbakov
- Biomedical Informatics Center, Department of Public Health Sciences, Medical University of South Carolina
| | - Abolfazl Mollalo
- Biomedical Informatics Center, Department of Public Health Sciences, Medical University of South Carolina
| | - Leslie Lenert
- Biomedical Informatics Center, Department of Public Health Sciences, Medical University of South Carolina
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Naeimi R, Sepidarkish M, Mollalo A, Parsa H, Mahjour S, Safarpour F, Almukhtar M, Mechaal A, Chemaitelly H, Sartip B, Marhoommirzabak E, Ardekani A, Hotez PJ, Gasser RB, Rostami A. SARS-CoV-2 seroprevalence in children worldwide: A systematic review and meta-analysis. EClinicalMedicine 2023; 56:101786. [PMID: 36590788 PMCID: PMC9795163 DOI: 10.1016/j.eclinm.2022.101786] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/30/2022] [Revised: 11/28/2022] [Accepted: 11/29/2022] [Indexed: 12/29/2022] Open
Abstract
BACKGROUND The higher hospitalisation rates of those aged 0-19 years (referred to herein as 'children') observed since the emergence of the immune-evasive SARS-CoV-2 Omicron variant and subvariants, along with the persisting vaccination disparities highlighted a need for in-depth knowledge of SARS-CoV-2 sero-epidemiology in children. Here, we conducted this systematic review to assess SARS-CoV-2 seroprevalence and determinants in children worldwide. METHODS In this systematic review and meta-analysis study, we searched international and preprinted scientific databases from December 1, 2019 to July 10, 2022. Pooled seroprevalences were estimated according to World Health Organization (WHO) regions (at 95% confidence intervals, CIs) using random-effects meta-analyses. Associations with SARS-CoV-2 seroprevalence and sources of heterogeneity were investigated using sub-group and meta-regression analyses. The protocol used in this study has been registered in PROSPERO (CRD42022350833). FINDINGS We included 247 studies involving 757,075 children from 70 countries. Seroprevalence estimates varied from 7.3% (5.8-9.1%) in the first wave of the COVID-19 pandemic to 37.6% (18.1-59.4%) in the fifth wave and 56.6% (52.8-60.5%) in the sixth wave. The highest seroprevalences in different pandemic waves were estimated for South-East Asia (17.9-81.8%) and African (17.2-66.1%) regions; while the lowest seroprevalence was estimated for the Western Pacific region (0.01-1.01%). Seroprevalence estimates were higher in children at older ages, in those living in underprivileged countries or regions, and in those of minority ethnic backgrounds. INTERPRETATION Our findings indicate that, by the end of 2021 and before the Omicron wave, around 50-70% of children globally were still susceptible to SARS-CoV-2 infection, clearly emphasising the need for more effective vaccines and better vaccination coverage among children and adolescents, particularly in developing countries and minority ethnic groups. FUNDING None.
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Affiliation(s)
- Reza Naeimi
- Infectious Diseases and Tropical Medicine Research Center, Health Research Institute, Babol University of Medical Sciences, Babol, Iran
| | - Mahdi Sepidarkish
- Department of Biostatistics and Epidemiology, School of Public Health, Babol University of Medical Sciences, Babol, Iran
| | - Abolfazl Mollalo
- Department of Public Health and Prevention Science, School of Health Sciences, Baldwin Wallace University, Berea, OH, USA
| | - Hamid Parsa
- Department of Neurology, University of Visayas, Gullas College of Medicine, Cebu City, 600 Cebu, Philippines
| | - Sanaz Mahjour
- Department of Psychiatry and Behavioral Sciences, Northwestern Feinberg School of Medicine, Chicago, IL, 60611, USA
| | - Fatemeh Safarpour
- Infectious Diseases and Tropical Medicine Research Center, Health Research Institute, Babol University of Medical Sciences, Babol, Iran
| | | | - Amal Mechaal
- Division of Hematology/Oncology, Department of Medicine, University of Illinois College of Medicine, Chicago, USA
| | - Hiam Chemaitelly
- Infectious Disease Epidemiology Group, Weill Cornell Medicine-Qatar, Cornell University, Doha, Qatar
- World Health Organization Collaborating Centre for Disease Epidemiology Analytics on HIV/AIDS, Sexually Transmitted Infections and Viral Hepatitis, Weill Cornell Medicine-Qatar, Qatar-Foundation-Education City, Cornell University, Doha, Qatar
- Department of Population Health Sciences, Weill Cornell Medicine, Cornell University, New York, USA
| | - Behnam Sartip
- Department of Psychiatry and Behavioral Sciences, Northwestern Feinberg School of Medicine, Chicago, IL, 60611, USA
| | - Elika Marhoommirzabak
- Department of Neurology, University of Visayas, Gullas College of Medicine, Cebu City, 600 Cebu, Philippines
| | - Ali Ardekani
- Health Policy Research Center, Institute of Health, Shiraz University of Medical Sciences, Shiraz, Iran
| | - Peter J. Hotez
- Texas Children's Hospital Center for Vaccine Development, Department of Pediatrics and Molecular Virology and Microbiology, National School of Tropical Medicine, Baylor College of Medicine, Houston, TX, USA
| | - Robin B. Gasser
- Department of Veterinary Biosciences, Melbourne Veterinary School, The University of Melbourne, Parkville, Victoria, Australia
- Corresponding author.
| | - Ali Rostami
- Infectious Diseases and Tropical Medicine Research Center, Health Research Institute, Babol University of Medical Sciences, Babol, Iran
- Corresponding author.
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Hasanpour AH, Sepidarkish M, Mollalo A, Ardekani A, Almukhtar M, Mechaal A, Hosseini SR, Bayani M, Javanian M, Rostami A. The global prevalence of methicillin-resistant Staphylococcus aureus colonization in residents of elderly care centers: a systematic review and meta-analysis. Antimicrob Resist Infect Control 2023; 12:4. [PMID: 36709300 PMCID: PMC9884412 DOI: 10.1186/s13756-023-01210-6] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2022] [Accepted: 01/21/2023] [Indexed: 01/30/2023] Open
Abstract
BACKGROUND Methicillin-resistant Staphylococcus aureus (MRSA) is a difficult to treat infection, particularly in residents of elderly care centers (ECCs). Despite the substantial burden of MRSA, an inadequate number of studies have analyzed MRSA prevalence in ECCs. OBJECTIVES We conducted a worldwide systematic review and meta-analysis on the prevalence and risk factors of MRSA in ECCs. METHODS We searched MEDLINE/PubMed, EMBASE, Web of Science, and Scopus databases and the gray literature sources for all studies published between January 1980 and December 2022 on the prevalence of MRSA in ECCs. A random-effects model was utilized to estimate pooled prevalence rates at 95% confidence intervals (CI). Moreover, the data were analyzed based on World Health Organization-defined regions, income, and human development index levels. RESULTS In total, 119 studies, including 164,717 participants from 29 countries, were found eligible for meta-analysis. The pooled global prevalence of MRSA was 14.69% (95% CI 12.39-17.15%; 16,793/164,717). Male gender [prevalence ratio (PR) = 1.55; 95% CI 1.47-1.64], previous MRSA infection (PR = 3.71; 95% CI 3.44-4.01), prior use of antibiotics (PR = 1.97; 95% CI 1.83-2.12), hospitalized within the previous year (PR = 1.32; 95% CI 1.20-1.45), have had any wound (PR = 2.38; 95% CI 2.23-2.55), have used urinary catheter (PR = 2.24; 95% CI 2.06-2.43), have used any medical device (PR = 1.78; 95% CI 1.66-1.91), and those with diabetes (PR = 1.55; CI 1.43-1.67) were more likely to be colonized by MRSA than other patients. CONCLUSION Screening programs and preventive measures should target MRSA in ECCs due to the high global prevalence rates.
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Affiliation(s)
- Amir Hossein Hasanpour
- grid.411495.c0000 0004 0421 4102Student Research Committee, Babol University of Medical Sciences, Babol, Iran
| | - Mahdi Sepidarkish
- grid.411495.c0000 0004 0421 4102Department of Biostatistics and Epidemiology, School of Public Health, Babol University of Medical Sciences, Babol, Iran
| | - Abolfazl Mollalo
- grid.252749.f0000 0001 1261 1616Department of Public Health and Prevention Science, School of Health Sciences, Baldwin Wallace University, Berea, OH USA
| | - Ali Ardekani
- grid.412571.40000 0000 8819 4698School of Medicine, Shiraz University of Medical Sciences, Shiraz, Iran
| | | | - Amal Mechaal
- grid.240145.60000 0001 2291 4776Department of Hematopoietic Biology and Malignancy, The University of Texas Md Anderson Cancer Center, Houston, TX USA
| | - Seyed Reza Hosseini
- grid.411495.c0000 0004 0421 4102Social Determinants of Health Research Center, Health Research Institute, Babol University of Medical Sciences, Babol, Iran
| | - Masoumeh Bayani
- grid.411495.c0000 0004 0421 4102Social Determinants of Health Research Center, Health Research Institute, Babol University of Medical Sciences, Babol, Iran
| | - Mostafa Javanian
- grid.411495.c0000 0004 0421 4102Infectious Diseases and Tropical Medicine Research Center, Health Research Institute, Babol University of Medical Sciences, Babol, Iran
| | - Ali Rostami
- Infectious Diseases and Tropical Medicine Research Center, Health Research Institute, Babol University of Medical Sciences, Babol, Iran.
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Alizadeh Khatir A, Sepidarkish M, Daryabari Y, Taghipour A, Mollalo A, Aghapour S, Rostami A. Malaria infection and the risk of epilepsy: a meta-analysis. Parasitology 2023; 150:1-9. [PMID: 36705577 PMCID: PMC10090621 DOI: 10.1017/s0031182022001780] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/19/2022] [Revised: 11/21/2022] [Accepted: 12/21/2022] [Indexed: 01/28/2023]
Abstract
Epilepsy, a chronic disease of the central nervous system, is highly prevalent in malaria-endemic regions. Therefore, several studies have evaluated the associations between malaria infection and epilepsy development. A meta-analysis of observational studies published from inception to 10 May 2022 has been conducted to synthesize and pool the existing data on this topic. The relevant publications were systematically searched in PubMed/Medline, Scopus, Embase and Web of Science database collections. A random-effects meta-analysis model (REM) was utilized to generate the pooled odds ratio (OR) at 95% confidence intervals (CIs). The between-studies heterogeneity was assessed with I2, as well as several subgroups, meta-regression and sensitivity analysis were performed to identify the source of heterogeneity. Overall, 17 eligible studies containing 6285 cases and 13 909 healthy controls were included. The REM showed a significant positive association between malaria infection and epilepsy development (OR 2.36; 95% CI 1.44–3.88). In subgroup analyses, significant positive associations were observed in studies that: epilepsy was the outcome in the follow-up of patients with cerebral malaria (OR 7.10; 95% CI 3.50–14.38); used blood smear to diagnose malaria (OR 4.80; 95% CI 2.36–9.77); included only children (OR 3.92; 95% CI 1.81–8.50); published before 2010 (OR 6.39; 95% CI 4.25–9.62). Our findings indicated that patients with malaria, especially those with cerebral malaria, are at a high risk of epilepsy development; however, further well-designed and controlled studies are needed to verify the strength of the association.
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Affiliation(s)
- Ali Alizadeh Khatir
- Mobility Impairment Research Center, Health Research Institute, Babol University of Medical Sciences, Babol, Iran
| | - Mahdi Sepidarkish
- Department of Biostatistics and Epidemiology, School of Public Health, Babol University of Medical Sciences, Babol, Iran
| | - Yasaman Daryabari
- Infectious Diseases and Tropical Medicine Research Center, Health Research Institute, Babol University of Medical Sciences, Babol, Iran
| | - Ali Taghipour
- Zoonoses Research Center, Jahrom University of Medical Sciences, Jahrom, Iran
| | - Abolfazl Mollalo
- Department of Public Health and Prevention Science, School of Health Sciences, Baldwin Wallace University, Berea, Ohio, USA
| | - Saeed Aghapour
- Department of Neurosurgery, Faculty of Medicine, Mazandaran University of Medical Sciences, Sari, Iran
| | - Ali Rostami
- Infectious Diseases and Tropical Medicine Research Center, Health Research Institute, Babol University of Medical Sciences, Babol, Iran
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8
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Vaezzadeh K, Sepidarkish M, Mollalo A, As'adi N, Rouholamin S, Rezaeinejad M, Mojtahedi MF, Hosseini SMM, Taheri M, Mahjour S, Mohammadi M, Chemaitelly H, Rostami A. Global prevalence of Neisseria gonorrhoeae infection in pregnant women: a systematic review and meta-analysis. Clin Microbiol Infect 2023; 29:22-31. [PMID: 35998807 DOI: 10.1016/j.cmi.2022.08.008] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2022] [Accepted: 08/09/2022] [Indexed: 12/27/2022]
Abstract
BACKGROUND Neisseria gonorrhoeae infection (gonorrhoea) is associated with several pregnancy complications, including preterm labour, spontaneous abortion, stillbirth, miscarriage, growth retardation, and intrauterine death. OBJECTIVES We performed a systematic review and meta-analysis to estimate the global and regional prevalence of gonorrhoea in pregnant women as a scientific basis for further studies. DATA SOURCES We systematically searched PubMed/MEDLINE, Web of Science, Embase, Scopus, and SciELO databases from inception to 10 July 2022. STUDY ELIGIBILITY CRITERIA We included cross-sectional, cohort, and case-control studies that reported the prevalence of gonorrhoea in pregnant women. In addition, we included baseline data for randomized controlled trials. PARTICIPANTS Pregnant women who were tested for gonorrhoea. METHODS Pooled prevalence estimates at 95% CIs were calculated using a random-effects meta-analysis model. We stratified countries according to WHO-defined regions and socio-economic factors. Moreover, sub-group-, meta-regression, and sensitivity analyses were conducted to investigate the effects of pre-determined factors on prevalence estimates and heterogeneity. RESULTS We identified 235 studies (249 datasets) on 19 104 175 pregnant women from 71 countries. The worldwide pooled prevalence of gonorrhoea in pregnant women was estimated at 1.85% (95% CI 1.73-1.97%), with the highest rate in the African region (3.53%) (2.84-4.29%) and the lowest rate in the European region (0.52%) (0.27-0.84%). Overall, the prevalence estimates were high among low-income countries (3.03%), pregnant women with HIV (2.81%), and pregnant women <20 years old (8.06%). A significant decreasing trend in prevalence was observed over time (β = -0.0008, 95% CI -0.0012 to -0.0004, p 0.001). DISCUSSION Our findings indicate that a substantial number of pregnant women have been infected with gonorrhoea globally, which calls for immediate public health measures to reduce the potential risk of infection. The study highlights the inadequacy or lack of data for many countries, emphasizing the need to expand systematic data collection efforts at national and regional levels.
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Affiliation(s)
- Kosar Vaezzadeh
- Infectious Diseases and Tropical Medicine Research Center, Health Research Institute, Babol University of Medical Sciences, Babol, Iran
| | - Mahdi Sepidarkish
- Department of Biostatistics and Epidemiology, School of Public Health, Babol University of Medical Sciences, Babol, Iran.
| | - Abolfazl Mollalo
- Department of Public Health and Prevention Science, School of Health Sciences, Baldwin Wallace University, Berea, Ohio, United States
| | - Nayereh As'adi
- Department of Midwifery, School of Nursing and Midwifery, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Safoura Rouholamin
- Department of Obstetrics and Gynecology, School of Medicine, Isfahan University of Medical Sciences, Isfahan, Iran
| | - Mahroo Rezaeinejad
- Department of Obstetrics and Gynecology, Imam Khomeini Hospital Complex, Tehran University of Medical Sciences, Tehran, Iran
| | - Maryam Farid Mojtahedi
- Department of Obstetrics and Gynecology, Arash Women's Hospital, Tehran University of Medical Sciences, Tehran, Iran
| | - Seyed Mohammad Mehdi Hosseini
- Department of Cellular and Molecular Biology, Faculty of Biological Science, Islamic Azad University, Tonekabon Branch, Iran
| | - Maryam Taheri
- Department of Biology, Science and Research Branch, Islamic Azad University, Tehran, Iran
| | - Sanaz Mahjour
- Northwestern Feinberg School of Medicine, Chicago, Illinois, United States
| | - Mohsen Mohammadi
- Non-Communicable Pediatric Diseases Research Center, Health Research Institute, Babol University of Medical Sciences, Babol, Iran
| | - Hiam Chemaitelly
- Infectious Disease Epidemiology Group, Weill Cornell Medicine-Qatar, Cornell University, Doha, Qatar; World Health Organization Collaborating Centre for Disease Epidemiology Analytics on HIV/AIDS, Sexually Transmitted Infections, and Viral Hepatitis, Weill Cornell Medicine-Qatar, Qatar-Foundation-Education City, Cornell University, Doha, Qatar; Department of Population Health Sciences, Weill Cornell Medicine, Cornell University, New York, NY, United States
| | - Ali Rostami
- Infectious Diseases and Tropical Medicine Research Center, Health Research Institute, Babol University of Medical Sciences, Babol, Iran.
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9
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Ardekani A, Sepidarkish M, Mollalo A, Afradiasbagharani P, Rouholamin S, Rezaeinejad M, Farid-Mojtahedi M, Mahjour S, Almukhtar M, Nourollahpour Shiadeh M, Rostami A. Worldwide prevalence of human papillomavirus among pregnant women: A systematic review and meta-analysis. Rev Med Virol 2023; 33:e2374. [PMID: 35678261 DOI: 10.1002/rmv.2374] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2022] [Revised: 05/15/2022] [Accepted: 05/25/2022] [Indexed: 01/28/2023]
Abstract
Human papillomavirus (HPV) is the causative agent of cervical cancer and a suspected agent for ovarian and endometrial cancers in women. It is associated with adverse outcomes during pregnancy. To date, there is no estimate of the prevalence of HPV infection in pregnant women at the regional and global levels. This study evaluated the global prevalence of HPV infection based on all observational studies that had reported the prevalence of HPV among pregnant women between January 1980 and December 2021 in PubMed/MEDLINE, Scopus, Web of Science, Embase, and SciELO databases. We utilised a random-effect model to determine the global prevalence and related risk factors of HPV infection. Between-studies heterogeneity was assessed using I2 statistic. Moreover, subgroup and meta-regression analyses were employed to assess the source of heterogeneity and the relationship between HPV prevalence and socio-demographic factors, respectively. Among 144 eligible studies comprising 189 datasets, the overall prevalence rates of HPV at the 95% confidence interval (CI) were estimated as 30.38% (26.88%-33.99%), 17.81% (9.81%-27.46%), 32.1% (25.09%-39.67%), 2.26% (0.1%-8.08%) and 25.5% (23.3%-27.8%) in cervico-vaginal, placenta, serum, amniotic fluid and urine samples, respectively. The highest prevalence rates were estimated for countries in the African region, while countries in the European and Eastern Mediterranean regions showed the lowest prevalence rates. HPV-16 and -18 were the most prevalent isolated strains. The pregnant women living with HIV and those with pregnancy disorders had significantly higher prevalence rates than general pregnant women (p < 0.05). The younger ages for first intercourse and pregnancy, multiple lifetime sexual partners, and lower education levels were primary risk factors for HPV infection. In conclusion, although the overall HPV prevalence varied markedly based on sampling sites and geographical locations, the highest prevalence rates were observed in less-developed countries. Our findings imply that implementing behavioural and therapeutic interventions as well as vaccination programs are crucial to prevent and reduce the current burden of HPV infection among pregnant women.
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Affiliation(s)
- Ali Ardekani
- Health Policy Research Center, Institute of Health, Shiraz University of Medical Sciences, Shiraz, Iran
| | - Mahdi Sepidarkish
- Department of Biostatistics and Epidemiology, School of Public Health, Babol University of Medical Sciences, Babol, Iran
| | - Abolfazl Mollalo
- Department of Public Health and Prevention Science, School of Health Sciences, Baldwin Wallace University, Berea, Ohio, USA
| | | | - Safoura Rouholamin
- Department of Obstetrics and Gynecology, School of Medicine, Isfahan University of Medical Sciences, Isfahan, Iran
| | - Mahroo Rezaeinejad
- Department of Obstetrics and Gynecology, Imam Khomeini Hospital Complex, Tehran University of Medical Sciences, Tehran, Iran
| | - Maryam Farid-Mojtahedi
- Department of Obstetrics and Gynecology, Endocrinology and Female Infertility Unit, Arash Women's Hospital, Tehran University of Medical Sciences, Tehran, Iran
| | - Sanaz Mahjour
- Department of Psychiatry and Behavioral Sciences, Northwestern Feinberg School of Medicine, Chicago, Illinois, USA
| | | | | | - Ali Rostami
- Infectious Diseases and Tropical Medicine Research Center, Health Research Institute, Babol University of Medical Sciences, Babol, Iran
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Holland C, Sepidarkish M, Deslyper G, Abdollahi A, Valizadeh S, Mollalo A, Mahjour S, Ghodsian S, Ardekani A, Behniafar H, Gasser RB, Rostami A. Global prevalence of Ascaris infection in humans (2010–2021): a systematic review and meta-analysis. Infect Dis Poverty 2022; 11:113. [PMCID: PMC9673379 DOI: 10.1186/s40249-022-01038-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2022] [Accepted: 10/13/2022] [Indexed: 11/21/2022] Open
Abstract
Background Ascariasis is one of the most important neglected tropical diseases of humans worldwide. The epidemiology of Ascaris infection appears to have changed with improvements in sanitation and mass drug administration, but there is no recent information on prevalence worldwide. Here, we performed a systematic review and meta-analysis to assess the global prevalence of human Ascaris infection from 2010 to 2021. Methods We searched MEDLINE/PubMed, and Scopus databases for studies measuring prevalence of Ascaris infection, published between 1 January 2010 and 1 January 2022. We included studies of the general human population in endemic regions, which used accepted coprodiagnostic methods, and excluded studies of people with occupations with an increased risk or probability of ascariasis and/or specific diseases other than ascariasis. We applied random-effects models to obtain pooled prevalence estimates for six sustainable development goal regions of the world. We extrapolated the prevalence estimates to the global population in 2020, to estimate the number of individuals with Ascaris infection. We conducted multiple subgroup and meta-regression analyses to explore possible sources of heterogeneity, and to assess relationships between prevalence estimates and demographic, socio-economic, geo-climatic factors. Results Of 11,245 studies screened, we analysed 758 prevalence estimates for a total number of 4,923,876 participants in 616 studies from 81 countries. The global prevalence estimated was 11.01% (95% confidence interval: 10.27–11.78%), with regional prevalences ranging from 28.77% (7.07–57.66%) in Melanesia (Oceania) to 1.39% (1.07–1.74%) in Eastern Asia. We estimated that ~ 732 (682–782) million people harboured Ascaris worldwide in 2021. The infected people in Latin America and the Caribbean region had a higher prevalence of high intensity infection (8.4%, 3.9–14.1%). Prevalence estimates were higher in children, and people in rural communities or in countries or regions with lower income and human development indices. There was a trend for a higher prevalence in regions with increasing mean annual relative humidity, precipitation and environmental temperature. Conclusions Our findings indicate that, despite a renewed commitment by some communities or authorities to control ascariasis, a substantial portion of the world’s human population (> 0.7 billion) is infected with Ascaris. Despite the clinical and socioeconomic importance of ascariasis, many past routine surveys did not assess the intensity of Ascaris infection in people. We propose that the present findings might stimulate the development of customised strategies for the improved control and prevention of Ascaris infection worldwide. Supplementary Information The online version contains supplementary material available at 10.1186/s40249-022-01038-z.
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Affiliation(s)
- Celia Holland
- grid.8217.c0000 0004 1936 9705Department of Zoology, School of Natural Sciences, Trinity College Dublin, College Green, Dublin 2, DO2PN40 Ireland
| | - Mahdi Sepidarkish
- grid.411495.c0000 0004 0421 4102Department of Biostatistics and Epidemiology, School of Public Health, Babol University of Medical Sciences, Babol, Iran
| | - Gwendoline Deslyper
- grid.8217.c0000 0004 1936 9705Department of Zoology, School of Natural Sciences, Trinity College Dublin, College Green, Dublin 2, DO2PN40 Ireland
| | - Ali Abdollahi
- grid.411463.50000 0001 0706 2472Department of Surgery, Faculty of Medicine, Tehran Medical Sciences, Islamic Azad University, Tehran, Iran
| | - Soghra Valizadeh
- grid.413026.20000 0004 1762 5445University of Mohaghegh Ardabili, Ardabil, Iran
| | - Abolfazl Mollalo
- grid.252749.f0000 0001 1261 1616Department of Public Health and Prevention Science, School of Health Sciences, Baldwin Wallace University, Berea, OH USA
| | - Sanaz Mahjour
- grid.16753.360000 0001 2299 3507Department of Psychiatry and Behavioral Sciences, Northwestern Feinberg School of Medicine, Chicago, IL 60611 USA
| | - Sahar Ghodsian
- grid.411600.2Department of Parasitology and Mycology, School of Medicine, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Ali Ardekani
- grid.412571.40000 0000 8819 4698Health Policy Research Center, Institute of Health, Shiraz University of Medical Sciences, Shiraz, Iran
| | - Hamed Behniafar
- Department of Medical Parasitology, Sarab Faculty of Medical Sciences, Sarab, East Azerbaijan Iran
| | - Robin B. Gasser
- grid.1008.90000 0001 2179 088XDepartment of Veterinary Biosciences, Melbourne Veterinary School, Faculty of Veterinary and Agricultural Sciences, The University of Melbourne, Parkville, VIC Australia
| | - Ali Rostami
- grid.411495.c0000 0004 0421 4102Infectious Diseases and Tropical Medicine Research Center, Health Research Institute, Babol University of Medical Sciences, Babol, Iran
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11
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Rostami A, Riahi SM, Mollalo A, Razavian I, Akbari N, Marhoommirzabak E, Mahjour S, Sartip B, Arshadi M, Razavian E, Ardekani A. Does latent Toxoplasma infection have a protective effect against developing multiple sclerosis? Evidence from an updated meta-analysis. Trans R Soc Trop Med Hyg 2022; 116:996-1006. [PMID: 35696089 DOI: 10.1093/trstmh/trac053] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2022] [Revised: 03/14/2022] [Accepted: 05/17/2022] [Indexed: 01/19/2023] Open
Abstract
Previous epidemiologic evidence suggests a protective effect of Toxoplasma gondii infection against multiple sclerosis (MS) development; however, inconsistent findings have been reported in this regard. Therefore, we performed an updated meta-analysis of observational studies to investigate the association of To. gondii infection with MS development. We searched all articles published in PubMed, Scopus, Embase and Web of Science databases as of 20 December 2021. A random effects meta-analysis model was used to generate the pooled OR at 95% CIs. The heterogeneity between studies was assessed using I2 and Cochran's Q statistics. Moreover, the likelihood of publication bias was determined by Egger's regression test. A total of 11 studies were eligible for meta-analysis, including 1172 MS cases and 1802 controls. Our findings indicated that 29.8% (95% CI 22.8 to 37.2%) of MS patients were seropositive for To. gondii infection, compared with 34.2% (95% CI 21.9 to 47.6%) of control subjects. The estimated pooled OR was 0.79 (95% CI 0.49 to 1.26), suggesting a non-significant negative association between To. gondii infection and MS development (p>0.05). The current study does not support the significant protective role of To. gondii infection on MS development. Our findings imply that further well-designed epidemiological and mechanistic studies are warranted to ascertain the possible association between To. gondii infection and MS and to exclude the potential confounders.
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Affiliation(s)
- Ali Rostami
- Infectious Diseases and Tropical Medicine Research Center, Health Research Institute, Babol University of Medical Sciences, Babol, Iran
| | - Seyed Mohammad Riahi
- Cardiovascular Diseases Research Center, Department of Epidemiology and Biostatistics, School of Medicine, Birjand University of Medical Sciences, Birjand, Iran
| | - Abolfazl Mollalo
- Department of Public Health and Prevention Science, School of Health Sciences, Baldwin Wallace University, Berea, Ohio, USA
| | - Iman Razavian
- Department of Neurosurgery, Functional Neurosurgery Research Center, Shohada Tajrish Hospital, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Nahid Akbari
- Department of Genetic, Faculty of Basic Science, Islamic Azad University, Varamin Pishva Branch, Tehran, Iran
| | - Elika Marhoommirzabak
- Department of Neurology, University of Visayas, Gullas College of Medicine, Cebu city, 600 Cebu, Philippines
| | - Sanaz Mahjour
- Department of Psychiatry and Behavioral Sciences, Northwestern Feinberg School of Medicine, Chicago, IL 60611, USA
| | - Behnam Sartip
- Department of Internal Medicine, Zanjan University of Medical Sciences, Zanjan, Iran
| | - Mahdi Arshadi
- Department of Psychiatry and Behavioral Sciences, Northwestern Feinberg School of Medicine, Chicago, IL 60611, USA
| | - Elnaz Razavian
- Department of Neurology, Tehran Medical Sciences Branch, Islamic Azad University, Tehran, Iran
| | - Ali Ardekani
- Student Research Committee, Shiraz University of Medical Sciences, Shiraz, Iran
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12
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Rivera KM, Mollalo A. Spatial analysis and modelling of depression relative to social vulnerability index across the United States. Geospat Health 2022; 17. [PMID: 36047342 DOI: 10.4081/gh.2022.1132] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/13/2022] [Accepted: 08/09/2022] [Indexed: 06/15/2023]
Abstract
According to the Substance Abuse and Mental Health Services Administration, about 21 million adults in the US experience a major depressive episode. Depression is considered a primary risk factor for suicide. In the US, about 19.5% of adults are reported to be experiencing a depressive disorder, leading to over 45,000 deaths (14.0 deaths per 100,000) due to suicides. To our knowledge, no previous spatial analysis study of depression relative to the social vulnerability index has been performed across the nation. In this study, county-level depression prevalence and indicators were compiled. We analysed the geospatial distribution of depression prevalence based on ordinary least squares, geographically weighted regression, and multiscale geographically weighted regression models. Our findings indicated that the multiscale model could explain over 86% of the local variance of depression prevalence across the US based on per capita income, age 65 and older, belonging to a minority group (predominantly negative impacts), and disability (mainly positive effect). This study can provide valuable insights for public health professionals and policymakers to address depression disparities.
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Affiliation(s)
- Kiara M Rivera
- Department of Public Health and Prevention Science, School of Health Sciences, Baldwin Wallace University, Berea, OH.
| | - Abolfazl Mollalo
- Department of Public Health and Prevention Science, School of Health Sciences, Baldwin Wallace University, Berea, OH.
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13
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Nourollahpour Shiadeh M, Sepidarkish M, Mollalo A, As'adi N, Khani S, Shahhosseini Z, Danesh M, Esfandyari S, Mokdad AH, Rostami A. Worldwide prevalence of maternal methicillin-resistant Staphylococcus aureus colonization: A systematic review and meta-analysis. Microb Pathog 2022; 171:105743. [PMID: 36044936 DOI: 10.1016/j.micpath.2022.105743] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2022] [Revised: 08/23/2022] [Accepted: 08/24/2022] [Indexed: 11/16/2022]
Abstract
Methicillin-resistant Staphylococcus aureus (MRSA) infection during pregnancy can adversely influence the well-being of pregnant women, fetuses, and neonates. To our knowledge, there is no global data on the maternal prevalence of MRSA colonization. We conducted a systematic review and meta-analysis to estimate the global and regional prevalence rates of MRSA colonization among pregnant women. We searched international databases (i.e., MEDLINE/PubMed, EMBASE, Scopus, Web of Science collection, and SciELO) for studies published from inception to March 10, 2022. Observational population-based studies reporting MRSA colonization among pregnant women were eligible to be included. We utilized the random-effects meta-analyses to compute the pooled prevalence estimates of maternal colonization across studies at 95% confidence intervals (CIs). The heterogeneity was assessed by I2 statistic and the Cochran's Q test. Subgroup and meta-regression analyses were used to adjust for potential sources of heterogeneity. The data source regarding maternal MRSA colonization included 55 studies from 24 countries and 110,654 pregnant women. The worldwide pooled prevalence for maternal MRSA colonization was 3.23% (95% CI, 2.40-4.17%), with the highest and lowest colonization rates for Africa (9.13%, 4.36-15.34%) and Europe (0.79%, 0.28-1.51%), respectively. We estimated that nearly 4.5 million pregnant women are colonized with MRSA worldwide. MRSA colonization rates were higher among black ethnicity, multiparous women, pregnant women with prior MRSA infection, women with lower personal hygiene, and those living in lower-income and human development indices countries or regions. MRSA colonizes substantial numbers of pregnant women worldwide, with varying prevalence rates in different regions; however, further investigations are needed to recognize regional differences. Our findings emphasized the need for prevention efforts against MRSA to reduce the health risks among women and newborns.
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Affiliation(s)
| | - Mahdi Sepidarkish
- Department of Biostatistics and Epidemiology, School of Public Health, Babol University of Medical Sciences, Babol, Iran
| | - Abolfazl Mollalo
- Department of Public Health and Prevention Science, School of Health Sciences, Baldwin Wallace University, Berea, OH, USA
| | - Nayereh As'adi
- Department of Midwifery, School of Nursing and Midwifery, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Soghra Khani
- Sexual and Reproductive Health Research Center, Mazandaran University of Medical Sciences, Sari, Iran
| | - Zohreh Shahhosseini
- Sexual and Reproductive Health Research Center, Mazandaran University of Medical Sciences, Sari, Iran
| | - Mahmonir Danesh
- Sexual and Reproductive Health Research Center, Mazandaran University of Medical Sciences, Sari, Iran
| | - Sahar Esfandyari
- Department of Urology, College of Medicine, University of Illinois at Chicago, Chicago, IL, USA
| | - Ali H Mokdad
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA
| | - Ali Rostami
- Infectious Diseases and Tropical Medicine Research Center, Health Research Institute, Babol University of Medical Sciences, Babol, Iran
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14
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Sorkhi H, Mollalo A, Bijani A, Mehravar S, Pournasrollah M, Sadr Moharerpour S, Rostami A. Association between Toxoplasma gondii Infection and Nephrotic Syndrome Risk in Children: A Case-Control Study and Systematic Review. J Trop Pediatr 2022; 68:6660808. [PMID: 35950309 DOI: 10.1093/tropej/fmac067] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
Some evidence suggests toxoplasmosis as an etiology of nephrotic syndrome (NS) in children; however, no observational study evaluated this relationship. In a case-control study, we enrolled 35 children with NS and 37 healthy children. All participants were examined for anti-Toxoplasma immunoglobulin G and M (IgG and IgM) antibodies using enzyme-linked immunosorbent assay. We also systematically reviewed the literature to assess this relationship. Prevalence of anti-Toxoplasma IgG was 17.4% and 13.5% in cases and controls, respectively, indicating a non-significant association (adjusted odds ratio, 1.22, 95% confidence interval, 0.35-4.41). No subjects were seropositive for IgM. In a systematic review, we found that acute toxoplasmosis can induce NS in some children and anti-Toxoplasma treatment is effective in the remission of NS in these cases. In pediatrics with NS, acute toxoplasmosis should be considered as a neglected causative factor.
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Affiliation(s)
- Hadi Sorkhi
- Non-Communicable Pediatric Diseases Research Center, Health Research Institute, Babol University of Medical Sciences, Babol, Iran
| | - Abolfazl Mollalo
- Department of Public Health and Prevention Science, School of Health Sciences, Baldwin Wallace University, Berea, OH, USA
| | - Ali Bijani
- Social Determinants of Health Research Center, Health Research Institute, Babol University of Medical Sciences, Babol, Iran
| | - Saeed Mehravar
- Department of Epidemiology and Statistics, School of Public Health, Tehran University of Medical Science, Tehran, Iran
| | - Mohammad Pournasrollah
- Non-Communicable Pediatric Diseases Research Center, Health Research Institute, Babol University of Medical Sciences, Babol, Iran
| | - Sahar Sadr Moharerpour
- Non-Communicable Pediatric Diseases Research Center, Health Research Institute, Babol University of Medical Sciences, Babol, Iran
| | - Ali Rostami
- Infectious Diseases and Tropical Medicine Research Center, Health Research Institute, Babol University of Medical Sciences, Babol, Iran
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15
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Mollalo A, Mohammadi A, Mavaddati S, Kiani B. Spatial Analysis of COVID-19 Vaccination: A Scoping Review. Int J Environ Res Public Health 2021; 18:12024. [PMID: 34831801 PMCID: PMC8624385 DOI: 10.3390/ijerph182212024] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/06/2021] [Revised: 11/09/2021] [Accepted: 11/10/2021] [Indexed: 01/01/2023]
Abstract
Spatial analysis of COVID-19 vaccination research is increasing in recent literature due to the availability of COVID-19 vaccination data that usually contain location components. However, to our knowledge, no previous study has provided a comprehensive review of this research area. Therefore, in this scoping review, we examined the breadth of spatial and spatiotemporal vaccination studies to summarize previous findings, highlight research gaps, and provide guidelines for future research. We performed this review according to the five-stage methodological framework developed by Arksey and O'Malley. We screened all articles published in PubMed/MEDLINE, Scopus, and Web of Science databases, as of 21 September 2021, that had employed at least one form of spatial analysis of COVID-19 vaccination. In total, 36 articles met the inclusion criteria and were organized into four main themes: disease surveillance (n = 35); risk analysis (n = 14); health access (n = 16); and community health profiling (n = 2). Our findings suggested that most studies utilized preliminary spatial analysis techniques, such as disease mapping, which might not lead to robust inferences. Moreover, few studies addressed data quality, modifiable areal unit problems, and spatial dependence, highlighting the need for more sophisticated spatial and spatiotemporal analysis techniques.
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Affiliation(s)
- Abolfazl Mollalo
- Department of Public Health and Prevention Science, School of Health Sciences, Baldwin Wallace University, Berea, OH 44017, USA;
| | - Alireza Mohammadi
- Department of Geography and Urban Planning, Faculty of Social Sciences, University of Mohaghegh Ardabili, Ardabil 56199, Iran;
| | - Sara Mavaddati
- Faculty of Medicine & Surgery, Policlinic University Hospital of Bari Aldo Moro, 70124 Bari, Italy;
| | - Behzad Kiani
- Department of Medical Informatics, School of Medicine, Mashhad University of Medical Sciences, Mashhad 91779, Iran
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16
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Rostami A, Riahi SM, Esfandyari S, Habibpour H, Mollalo A, Mirzapour A, Behniafar H, MohammadiMoghadam S, Azizi Kyvanani N, Aghaei S, Bazrafshan N, Ghazvini S. Geo-climatic factors and prevalence of chronic toxoplasmosis in pregnant women: A meta-analysis and meta-regression. Environ Pollut 2021; 288:117790. [PMID: 34329056 DOI: 10.1016/j.envpol.2021.117790] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/22/2021] [Revised: 07/02/2021] [Accepted: 07/12/2021] [Indexed: 06/13/2023]
Abstract
In this study, we evaluated the effects of geo-climatic parameters and other potential risk factors on the prevalence of chronic toxoplasmosis (CT) in pregnant women. We searched PubMed/MEDLINE, Web of Science, EMBASE, Scopus, and SciELO databases for seroepidemiological studies published between January 1988, and February 2021. We performed meta-analysis and meta-regression by using a random effect model to synthesize data. A total of 360 eligible datasets, including 1,289,605 pregnant women from 94 countries, were included in this study. The highest and lowest prevalence rates were estimated for latitudes of 0-10° (49.4%) and ≥50° (26.8%); and for the longitude of 80-90° (44.2%) and 110-120° (7.8%), respectively. Concerning climatic parameters, the highest and lowest prevalence rates were estimated in regions with the mean relative humidities of >80% (46.6%) and <40% (27.0); annual precipitation between 1000 and 1500 mm (39.2%) and 250-500 mm (26.8%); and mean annual temperature of 20-30 °C (36.5%), and <7 °C (24.9%), respectively. Meta-regression analyses indicated significant increasing trends in prevalence of CT in pregnant women with decrease in geographical latitude (coefficient, = -0.0035), and geographical longitudes (C = -0.0017). While it was positively associated (P < 0.01) with the mean environmental temperature (C = 0.0047), annual precipitation (C = 0.000064), and mean relative humidity (C = 0.002). Our results highlighted various effects of environmental parameters on the prevalence of CT. Therefore, different regions in the world may benefit from different types of interventions, and thus, novel preventive measures in a region should be developed according to local climate, agricultural activities and people culture.
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Affiliation(s)
- Ali Rostami
- Infectious Diseases and Tropical Medicine Research Center, Health Research Institute, Babol University of Medical Sciences, Babol, Iran.
| | - Seyed Mohammad Riahi
- Cardiovascular Diseases Research Center, Department of Epidemiology and Biostatistics, School of Medicine, Birjand University of Medical Sciences, Birjand, Iran
| | - Sahar Esfandyari
- Department of Anatomy, School of Medicine, Tehran University of Medical Sciences, Tehran, Iran
| | - Haniyeh Habibpour
- Department of Microbiology, Islamic Azad University, Varamin Pishva Branch, Tehran, Iran
| | - Abolfazl Mollalo
- Department of Public Health and Prevention Science, School of Health Sciences, Baldwin Wallace University, Berea, OH, USA
| | - Aliyar Mirzapour
- Innovative Medical Research Center, Department of Medical Parasitology and Mycology, School of Medicine, Mashhad Branch, Islamic Azad University, Mashhad, Iran
| | - Hamed Behniafar
- Department of Medical Parasitology, Sarab Faculty of Medical Sciences, Sarab, Iran
| | | | | | - Shima Aghaei
- Department of Medical Mycology, Faculty of Medical Science, Tarbiat Modares University, Tehran, Iran
| | - Negar Bazrafshan
- Infectious Diseases and Tropical Medicine Research Center, Health Research Institute, Babol University of Medical Sciences, Babol, Iran
| | - Sobhan Ghazvini
- Infectious Diseases and Tropical Medicine Research Center, Health Research Institute, Babol University of Medical Sciences, Babol, Iran
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17
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Abedi SH, Fazlzadeh A, Mollalo A, Sartip B, Mahjour S, Bahadory S, Taghipour A, Rostami A. The neglected role of Blastocystis sp. and Giardia lamblia in development of irritable bowel syndrome: A systematic review and meta-analysis. Microb Pathog 2021; 162:105215. [PMID: 34592369 DOI: 10.1016/j.micpath.2021.105215] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2021] [Revised: 09/22/2021] [Accepted: 09/25/2021] [Indexed: 02/08/2023]
Abstract
The possible role of Blastocystis sp. and Giardia lamblia infections in the development of irritable bowel syndrome (IBS) has long been controversial. In this study, we conducted a systematic review and meta-analysis to investigate whether these protozoan infections are associated with IBS development. We systematically searched international databases for all studies that reported these protozoa in IBS patients published by May 10, 2021. Studies were included in the review if they were observational studies with confirmed patients with IBS (in case-control and cross-sectional studies) or parasitic infections (cohort studies) with an appropriate control group. Pooled odds ratios (ORs) and 95% confidence intervals were estimated using a random-effects meta-analysis model for included studies. A total of 32 papers (42 datasets), including 29 papers (31 datasets) for Blastocystis sp./IBS and 11 papers (11 datasets) for G. lamblia/IBS met the eligibility criteria. Our results indicated that the individuals with Blastocystis sp. infection were significantly at a higher risk of IBS development (OR, 1.78; 95%CI, 1.29-2.44). Moreover, cohort studies indicated a significant positive association between G. lamblia infection and IBS risk (OR, 5.47; 95%CI, 4.23-7.08); while an increasing but no statistically significant risk was observed in case-control studies (OR, 1.19; 95%CI, 0.75-1.87). Our findings suggested that Blastocystis sp. and G. lamblia infections are associated with the increased risk of developing IBS. Despite these results, further studies are needed to determine the effect of these protozoa on IBS development.
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Affiliation(s)
- Seyed Hasan Abedi
- Cancer Research Center, Health Research Institute, Babol University of Medical Sciences, Babol, Iran
| | - Aylar Fazlzadeh
- Department of Internal Medicine, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Abolfazl Mollalo
- Department of Public Health and Prevention Science, School of Health Sciences, Baldwin Wallace University, Berea, OH, USA
| | - Behnam Sartip
- Department of Internal Medicine, Zanjan University of Medical Sciences, Zanjan, Iran
| | - Sanaz Mahjour
- Department of Psychiatry and Behavioral Sciences, Northwestern Feinberg School of Medicine, Chicago, IL, 60611, USA
| | - Saeed Bahadory
- Department of Parasitology, Faculty of Medical Sciences, Tarbiat Modares University, Tehran, Iran
| | - Ali Taghipour
- Zoonoses Research Center, School of Medicine, Jahrom University of Medical Sciences, Jahrom, Iran.
| | - Ali Rostami
- Infectious Diseases and Tropical Medicine Research Center, Health Research Institute, Babol University of Medical Sciences, Babol, Iran.
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18
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Mohammadi A, Mollalo A, Bergquist R, Kiani B. Measuring COVID-19 vaccination coverage: an enhanced age-adjusted two-step floating catchment area model. Infect Dis Poverty 2021; 10:118. [PMID: 34530923 PMCID: PMC8443959 DOI: 10.1186/s40249-021-00904-6] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/16/2021] [Accepted: 09/03/2021] [Indexed: 11/30/2022] Open
Abstract
BACKGROUND There are only limited studies on access to COVID-19 vaccines and identifying the most appropriate health centres for performing vaccination in metropolitan areas. This study aimed to measure potential spatial access to COVID-19 vaccination centres in Mashhad, the second-most populous city in Iran. METHODS The 2021 age structure of the urban census tracts was integrated into the enhanced two-step floating catchment area model to improve accuracy. The model was developed based on three different access scenarios: only public hospitals, only public healthcare centres and both (either hospitals or healthcare centres) as potential vaccination facilities. The weighted decision-matrix and analytic hierarchy process, based on four criteria (i.e. service area, accessibility index, capacity of vaccination centres and distance to main roads), were used to choose potential vaccination centres looking for the highest suitability for residents. Global Moran's index (GMI) was used to measure the spatial autocorrelation of the accessibility index in different scenarios and the proposed model. RESULTS There were 26 public hospitals and 271 public healthcare centres in the study area. Although the exclusive use of public healthcare centres for vaccination can provide the highest accessibility in the eastern and north-eastern parts of the study area, our findings indicate that including both public hospitals and public healthcare centres provide high accessibility to vaccination in central urban part. Therefore, a combination of public hospitals and public healthcare centres is recommended for efficient vaccination coverage. The value of GMI for the proposed model (accessibility to selected vaccination centres) was calculated as 0.53 (Z = 162.42, P < 0.01). Both GMI and Z-score values decreased in the proposed model, suggesting an enhancement in accessibility to COVID-19 vaccination services. CONCLUSIONS The periphery and poor areas of the city had the least access to COVID-19 vaccination centres. Measuring spatial access to COVID-19 vaccination centres can provide valuable insights for urban public health decision-makers. Our model, coupled with geographical information systems, provides more efficient vaccination coverage by identifying the most suitable healthcare centres, which is of special importance when only few centres are available.
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Affiliation(s)
- Alireza Mohammadi
- Department of Geography and Urban Planning, Faculty of Social Sciences, University of Mohaghegh Ardabili, Ardabil, Iran
| | - Abolfazl Mollalo
- Department of Public Health and Prevention Science, School of Health Sciences, Baldwin Wallace University, Berea, OH, USA
| | - Robert Bergquist
- Ingerod, Brastad, Sweden (formerly with the UNICEF/UNDP/World Bank/WHO Special Programme for Research and Training in Tropical Diseases, World Health Organization), Geneva, Switzerland
| | - Behzad Kiani
- Department of Medical Informatics, School of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran.
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19
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Mollalo A, Tatar M. Spatial Modeling of COVID-19 Vaccine Hesitancy in the United States. Int J Environ Res Public Health 2021; 18:9488. [PMID: 34574416 PMCID: PMC8467210 DOI: 10.3390/ijerph18189488] [Citation(s) in RCA: 29] [Impact Index Per Article: 9.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/15/2021] [Revised: 09/05/2021] [Accepted: 09/07/2021] [Indexed: 12/13/2022]
Abstract
Vaccine hesitancy refers to delay in acceptance or refusal of vaccines despite the availability of vaccine services. Despite the efforts of United States healthcare providers to vaccinate the bulk of its population, vaccine hesitancy is still a severe challenge that has led to the resurgence of COVID-19 cases to over 100,000 people during early August 2021. To our knowledge, there are limited nationwide studies that examined the spatial distribution of vaccination rates, mainly based on the social vulnerability index (SVI). In this study, we compiled a database of the percentage of fully vaccinated people at the county scale across the continental United States as of 29 July 2021, along with SVI data as potential significant covariates. We further employed multiscale geographically weighted regression to model spatial nonstationarity of vaccination rates. Our findings indicated that the model could explain over 79% of the variance of vaccination rate based on Per capita income and Minority (%) (with positive impacts), and Age 17 and younger (%), Mobile homes (%), and Uninsured people (%) (with negative effects). However, the impact of each covariate varied for different counties due to using separate optimal bandwidths. This timely study can serve as a geospatial reference to support public health decision-makers in forming region-specific policies in monitoring vaccination programs from a geographic perspective.
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Affiliation(s)
- Abolfazl Mollalo
- Department of Public Health and Prevention Science, School of Health Sciences, Baldwin Wallace University, Berea, OH 44017, USA
| | - Moosa Tatar
- Matheson Center for Health Care Studies, University of Utah, Salt Lake City, UT 84108, USA;
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20
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Mollalo A, Rivera KM, Vahabi N. Spatial statistical analysis of pre-existing mortalities of 20 diseases with COVID-19 mortalities in the continental United States. Sustain Cities Soc 2021; 67:102738. [PMID: 33532175 PMCID: PMC7843116 DOI: 10.1016/j.scs.2021.102738] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/28/2020] [Revised: 11/30/2020] [Accepted: 12/18/2020] [Indexed: 05/14/2023]
Abstract
BACKGROUND Although the United States is among the countries with the highest mortalities of COVID-19, inadequate geospatial studies have analyzed the disease mortalities across the nation. METHODS In this county-level study, we investigated age-adjusted co-mortalities of 20 diseases, including cardiovascular, cancer, drug and alcohol disorder, respiratory and infectious diseases with COVID-19 over the first ten months of epidemic. One-way analysis of variance was applied to the Local Moran's I classes (High-High and Low-Low clusters, and non-significant counties of COVID-19) to examine whether the mean mortality measures of covariates that fall into the classes are significantly different. Moreover, a mixed-effects multinomial logistic regression model was employed to estimate the effects of mortalities on COVID-19 classes. RESULTS Results showed that the distribution of COVID-19 case fatality ratio (CFR) and mortality rate co-occurrence of High-High clusters were mainly concentrated in Louisiana, Connecticut, and New Jersey. Also, positive associations were observed between High-High cluster of COVID-19 CFR and Asthma (OR = 4.584, 95 % Confidence Interval (CI): 2.583-8.137), Hepatitis (OR = 5.602, CI: 1.265-24.814) and Leukemia (OR = 2.172, CI: 1.518-3.106) mortality rates compared to the non-significant counties, respectively. CONCLUSIONS Our results indicated that counties with higher mortality of some cancers and respiratory diseases are more vulnerable to fall into clusters of HH COVID-19 CFR. Future vaccine allocation and more medical professionals and treatment equipment should be a priority to those High-High clusters.
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Affiliation(s)
- Abolfazl Mollalo
- Department of Public Health and Prevention Science, School of Health Sciences, Baldwin Wallace University, Berea, OH, USA
| | - Kiara M Rivera
- Department of Public Health and Prevention Science, School of Health Sciences, Baldwin Wallace University, Berea, OH, USA
| | - Nasim Vahabi
- Informatics Institute, University of Florida, Gainesville, FL, USA
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21
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Vahabi N, Salehi M, Duarte JD, Mollalo A, Michailidis G. County-level longitudinal clustering of COVID-19 mortality to incidence ratio in the United States. Sci Rep 2021; 11:3088. [PMID: 33542313 PMCID: PMC7862666 DOI: 10.1038/s41598-021-82384-0] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2020] [Accepted: 01/18/2021] [Indexed: 01/30/2023] Open
Abstract
As of November 12, 2020, the mortality to incidence ratio (MIR) of COVID-19 was 5.8% in the US. A longitudinal model-based clustering system on the disease trajectories over time was used to identify "vulnerable" clusters of counties that would benefit from allocating additional resources by federal, state and county policymakers. County-level COVID-19 cases and deaths, together with a set of potential risk factors were collected for 3050 U.S. counties during the 1st wave of COVID-19 (Mar25-Jun3, 2020), followed by similar data for 1344 counties (in the "sunbelt" region of the country) during the 2nd wave (Jun4-Sep2, 2020), and finally for 1055 counties located broadly in the great plains region of the country during the 3rd wave (Sep3-Nov12, 2020). We used growth mixture models to identify clusters of counties exhibiting similar COVID-19 MIR growth trajectories and risk-factors over time. The analysis identifies "more vulnerable" clusters during the 1st, 2nd and 3rd waves of COVID-19. Further, tuberculosis (OR 1.3-2.1-3.2), drug use disorder (OR 1.1), hepatitis (OR 13.1), HIV/AIDS (OR 2.3), cardiomyopathy and myocarditis (OR 1.3), diabetes (OR 1.2), mesothelioma (OR 9.3) were significantly associated with increased odds of being in a more vulnerable cluster. Heart complications and cancer were the main risk factors increasing the COVID-19 MIR (range 0.08-0.52% MIR↑). We identified "more vulnerable" county-clusters exhibiting the highest COVID-19 MIR trajectories, indicating that enhancing the capacity and access to healthcare resources would be key to successfully manage COVID-19 in these clusters. These findings provide insights for public health policymakers on the groups of people and locations they need to pay particular attention while managing the COVID-19 epidemic.
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Affiliation(s)
- Nasim Vahabi
- Informatics Institute, University of Florida, Gainesville, FL, USA
| | - Masoud Salehi
- Department of Biostatistics, College of Public Health, Iran University of Medical Sciences, Tehran, Iran
| | - Julio D Duarte
- Center for Pharmacogenomics, Department of Pharmacotherapy and Translational Research, College of Pharmacy, University of Florida, Gainesville, FL, USA
| | - Abolfazl Mollalo
- Department of Public Health and Prevention Sciences, School of Health Sciences, Baldwin Wallace University, Berea, OH, USA
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22
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Mollalo A, Vahedi B, Bhattarai S, Hopkins LC, Banik S, Vahedi B. Predicting the hotspots of age-adjusted mortality rates of lower respiratory infection across the continental United States: Integration of GIS, spatial statistics and machine learning algorithms. Int J Med Inform 2020; 142:104248. [PMID: 32871492 PMCID: PMC7442929 DOI: 10.1016/j.ijmedinf.2020.104248] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2020] [Revised: 07/25/2020] [Accepted: 08/10/2020] [Indexed: 12/21/2022]
Abstract
Lower respiratory infections (LRI) are the cause of a significant number of hospitalizations in the US. No previous nationwide study examined geographic variations of LRI mortality rates and their association with underlying factors. There was a shift in the location of LRI hotspots from west coast to southeast over time. Decision tree classifiers could predict LRI mortality hotspots with high accuracies. Higher spring temperature and increased precipitation during winter were among the most substantial predictors of presence or absence of LRI hotspots.
Objective Although lower respiratory infections (LRI) are among the leading causes of mortality in the US, their association with underlying factors and geographic variation have not been adequately examined. Methods In this study, explanatory variables (n = 46) including climatic, topographic, socio-economic, and demographic factors were compiled at the county level across the continentalUS.Machine learning algorithms - logistic regression (LR), random forest (RF), gradient boosting decision trees (GBDT), k-nearest neighbors (KNN), and support vector machine (SVM) - were employed to predict the presence/absence of hotspots (P < 0.05) for elevated age-adjusted LRI mortality rates in a geographic information system framework. Results Overall, there was a historical shift in hotspots away from the western US into the southeastern parts of the country and they were highly localized in a few counties. The two decision tree methods (RF and GBDT) outperformed the other algorithms (accuracies: 0.92; F1-scores: 0.85 and 0.84; area under the precision-recall curve: 0.84 and 0.83, respectively). Moreover, the results of the RF and GBDT indicated that higher spring minimum temperature, increased winter precipitation, and higher annual median household income were among the most substantial factors in predicting the hotspots. Conclusions This study helps raise awareness of public health decision-makers to develop and target LRI prevention programs.
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Affiliation(s)
- Abolfazl Mollalo
- Department of Public Health and Prevention Science, School of Health Sciences, Baldwin Wallace University, Berea, OH, USA.
| | - Behrooz Vahedi
- Department of Mathematics, University of Trento, Trento, Italy.
| | | | - Laura C Hopkins
- Department of Public Health and Prevention Science, School of Health Sciences, Baldwin Wallace University, Berea, OH, USA.
| | - Swagata Banik
- Department of Public Health and Prevention Science, School of Health Sciences, Baldwin Wallace University, Berea, OH, USA.
| | - Behzad Vahedi
- Department of Geography, University of Colorado Boulder, Boulder, CO, USA.
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23
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Abstract
During the first 90 days of the COVID-19 outbreak in the United States, over 675,000 confirmed cases of the disease have been reported, posing unprecedented socioeconomic burden to the country. Due to inadequate research on geographic modeling of COVID-19, we investigated county-level variations of disease incidence across the continental United States. We compiled a geodatabase of 35 environmental, socioeconomic, topographic, and demographic variables that could explain the spatial variability of disease incidence. Further, we employed spatial lag and spatial error models to investigate spatial dependence and geographically weighted regression (GWR) and multiscale GWR (MGWR) models to locally examine spatial non-stationarity. The results suggested that even though incorporating spatial autocorrelation could significantly improve the performance of the global ordinary least square model, these models still represent a significantly poor performance compared to the local models. Moreover, MGWR could explain the highest variations (adj. R2: 68.1%) with the lowest AICc compared to the others. Mapping the effects of significant explanatory variables (i.e., income inequality, median household income, the proportion of black females, and the proportion of nurse practitioners) on spatial variability of COVID-19 incidence rates using MGWR could provide useful insights to policymakers for targeted interventions.
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Affiliation(s)
- Abolfazl Mollalo
- Department of Public Health and Prevention Sciences, School of Health Sciences, Baldwin Wallace University, Berea, OH, USA.
| | - Behzad Vahedi
- Department of Geography, University of California Santa Barbara (UCSB), Santa Barbara, CA, USA.
| | - Kiara M Rivera
- Department of Public Health and Prevention Sciences, School of Health Sciences, Baldwin Wallace University, Berea, OH, USA.
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24
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Mollalo A, Vahedi B, Rivera KM. GIS-based spatial modeling of COVID-19 incidence rate in the continental United States. Sci Total Environ 2020; 728:138884. [PMID: 32335404 PMCID: PMC7175907 DOI: 10.1016/j.scitotenv.2020.138884] [Citation(s) in RCA: 298] [Impact Index Per Article: 74.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/18/2020] [Revised: 04/19/2020] [Accepted: 04/20/2020] [Indexed: 04/14/2023]
Abstract
During the first 90 days of the COVID-19 outbreak in the United States, over 675,000 confirmed cases of the disease have been reported, posing unprecedented socioeconomic burden to the country. Due to inadequate research on geographic modeling of COVID-19, we investigated county-level variations of disease incidence across the continental United States. We compiled a geodatabase of 35 environmental, socioeconomic, topographic, and demographic variables that could explain the spatial variability of disease incidence. Further, we employed spatial lag and spatial error models to investigate spatial dependence and geographically weighted regression (GWR) and multiscale GWR (MGWR) models to locally examine spatial non-stationarity. The results suggested that even though incorporating spatial autocorrelation could significantly improve the performance of the global ordinary least square model, these models still represent a significantly poor performance compared to the local models. Moreover, MGWR could explain the highest variations (adj. R2: 68.1%) with the lowest AICc compared to the others. Mapping the effects of significant explanatory variables (i.e., income inequality, median household income, the proportion of black females, and the proportion of nurse practitioners) on spatial variability of COVID-19 incidence rates using MGWR could provide useful insights to policymakers for targeted interventions.
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Affiliation(s)
- Abolfazl Mollalo
- Department of Public Health and Prevention Sciences, School of Health Sciences, Baldwin Wallace University, Berea, OH, USA.
| | - Behzad Vahedi
- Department of Geography, University of California Santa Barbara (UCSB), Santa Barbara, CA, USA.
| | - Kiara M Rivera
- Department of Public Health and Prevention Sciences, School of Health Sciences, Baldwin Wallace University, Berea, OH, USA.
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25
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Mollalo A, Rivera KM, Vahedi B. Artificial Neural Network Modeling of Novel Coronavirus (COVID-19) Incidence Rates across the Continental United States. Int J Environ Res Public Health 2020; 17:ijerph17124204. [PMID: 32545581 PMCID: PMC7344609 DOI: 10.3390/ijerph17124204] [Citation(s) in RCA: 72] [Impact Index Per Article: 18.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/21/2020] [Revised: 06/08/2020] [Accepted: 06/10/2020] [Indexed: 12/23/2022]
Abstract
Prediction of the COVID-19 incidence rate is a matter of global importance, particularly in the United States. As of 4 June 2020, more than 1.8 million confirmed cases and over 108 thousand deaths have been reported in this country. Few studies have examined nationwide modeling of COVID-19 incidence in the United States particularly using machine-learning algorithms. Thus, we collected and prepared a database of 57 candidate explanatory variables to examine the performance of multilayer perceptron (MLP) neural network in predicting the cumulative COVID-19 incidence rates across the continental United States. Our results indicated that a single-hidden-layer MLP could explain almost 65% of the correlation with ground truth for the holdout samples. Sensitivity analysis conducted on this model showed that the age-adjusted mortality rates of ischemic heart disease, pancreatic cancer, and leukemia, together with two socioeconomic and environmental factors (median household income and total precipitation), are among the most substantial factors for predicting COVID-19 incidence rates. Moreover, results of the logistic regression model indicated that these variables could explain the presence/absence of the hotspots of disease incidence that were identified by Getis-Ord Gi* (p < 0.05) in a geographic information system environment. The findings may provide useful insights for public health decision makers regarding the influence of potential risk factors associated with the COVID-19 incidence at the county level.
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Affiliation(s)
- Abolfazl Mollalo
- Department of Public Health and Prevention Sciences, School of Health Sciences, Baldwin Wallace University, Berea, OH 44017, USA;
- Correspondence:
| | - Kiara M. Rivera
- Department of Public Health and Prevention Sciences, School of Health Sciences, Baldwin Wallace University, Berea, OH 44017, USA;
| | - Behzad Vahedi
- Department of Geography, University of California Santa Barbara (UCSB), Santa Barbara, CA 93106, USA;
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26
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Mollalo A, Mao L, Rashidi P, Glass GE. A GIS-Based Artificial Neural Network Model for Spatial Distribution of Tuberculosis across the Continental United States. Int J Environ Res Public Health 2019; 16:ijerph16010157. [PMID: 30626123 PMCID: PMC6338935 DOI: 10.3390/ijerph16010157] [Citation(s) in RCA: 47] [Impact Index Per Article: 9.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/22/2018] [Revised: 12/05/2018] [Accepted: 12/28/2018] [Indexed: 01/20/2023]
Abstract
Despite the usefulness of artificial neural networks (ANNs) in the study of various complex problems, ANNs have not been applied for modeling the geographic distribution of tuberculosis (TB) in the US. Likewise, ecological level researches on TB incidence rate at the national level are inadequate for epidemiologic inferences. We collected 278 exploratory variables including environmental and a broad range of socio-economic features for modeling the disease across the continental US. The spatial pattern of the disease distribution was statistically evaluated using the global Moran’s I, Getis–Ord General G, and local Gi* statistics. Next, we investigated the applicability of multilayer perceptron (MLP) ANN for predicting the disease incidence. To avoid overfitting, L1 regularization was used before developing the models. Predictive performance of the MLP was compared with linear regression for test dataset using root mean square error, mean absolute error, and correlations between model output and ground truth. Results of clustering analysis showed that there is a significant spatial clustering of smoothed TB incidence rate (p < 0.05) and the hotspots were mainly located in the southern and southeastern parts of the country. Among the developed models, single hidden layer MLP had the best test accuracy. Sensitivity analysis of the MLP model showed that immigrant population (proportion), underserved segments of the population, and minimum temperature were among the factors with the strongest contributions. The findings of this study can provide useful insight to health authorities on prioritizing resource allocation to risk-prone areas.
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Affiliation(s)
- Abolfazl Mollalo
- Department of Geography, University of Florida, 3141 Turlington Hall, P.O. Box 117315, Gainesville, FL 32611, USA.
| | - Liang Mao
- Department of Geography, University of Florida, 3141 Turlington Hall, P.O. Box 117315, Gainesville, FL 32611, USA.
| | - Parisa Rashidi
- Department of Biomedical Engineering, University of Florida, 1064 Center Drive, NEB 459, Gainesville, FL 32611, USA.
| | - Gregory E Glass
- Department of Geography, University of Florida, 3141 Turlington Hall, P.O. Box 117315, Gainesville, FL 32611, USA.
- Emerging Pathogens Institute, University of Florida, Gainesville, FL 32611, USA.
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27
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Mollalo A, Blackburn JK, Morris LR, Glass GE. A 24-year exploratory spatial data analysis of Lyme disease incidence rate in Connecticut, USA. Geospat Health 2017; 12:588. [PMID: 29239560 DOI: 10.4081/gh.2017.588] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/26/2017] [Revised: 07/14/2017] [Accepted: 08/01/2017] [Indexed: 05/05/2023]
Abstract
Despite efforts to control Lyme disease in Connecticut, USA, it remains endemic in many towns, posing a heavy burden. We examined changes in the spatial distribution of significant spatial clusters of Lyme disease incidence rates at the town level from 1991 to 2014 as an approach for targeted interventions. Lyme disease data were grouped into four discrete time periods and incidence rates were smoothed with Empirical Bayes estimation in GeoDa. Local clustering was measured using a local indicator of spatial autocorrelation (LISA). Elliptic spatial scan statistics (SSS) in different shapes and directions were also performed in SaTScan. The accuracy of these two cluster detection methods was assessed and compared for sensitivity, specificity, and overall accuracy. There was significant clustering during each period and significant clusters persisted predominantly in western and eastern parts of the state. Generally, the SSS method was more sensitive, while LISA was more specific with higher overall accuracy in identifying clusters. Even though the location of clusters changed over time, some towns were persistently (across all four periods) identified as clusters in LISA and their neighbouring towns (three of four periods) in SSS suggesting these regions should be prioritized for targeted interventions.
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Affiliation(s)
- Abolfazl Mollalo
- Department of Geography, University of Florida, Gainesville, FL.
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28
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Sofizadeh A, Rassi Y, Vatandoost H, Hanafi-Bojd AA, Mollalo A, Rafizadeh S, Akhavan AA. Predicting the Distribution of Phlebotomus papatasi (Diptera: Psychodidae), the Primary Vector of Zoonotic Cutaneous Leishmaniasis, in Golestan Province of Iran Using Ecological Niche Modeling: Comparison of MaxEnt and GARP Models. J Med Entomol 2017; 54:312-320. [PMID: 28025245 DOI: 10.1093/jme/tjw178] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/28/2016] [Accepted: 10/04/2016] [Indexed: 06/06/2023]
Abstract
Zoonotic cutaneous leishmaniasis (ZCL) is a prevalent vector-borne disease in the Golestan province of Iran, with Phlebotomus papatasi (Scopoli, 1786) serving as the main vector. The aim of this study was to model the probability of presence of this species in the study area, and to determine the underlying factors affecting its distribution. Three villages were selected from each county of the province and visited monthly for investigating ZCL. Sticky paper traps were used for collecting the sand flies to determine the species present. The presence of Ph. papatasi was modeled using genetic algorithm for rule-set production (GARP) and maximum entropy (MaxEnt) techniques. Both models showed the central and northern parts of the province with lowland areas were more vulnerable to Ph. papatasi propagation, in comparison with the southern parts with mountainous and forest areas. The area under curve (AUC) of MaxEnt model for the training points was calculated as 0.90, indicating excellent performance of the model in predicting Ph. papatasi distribution. Jackknife test showed that the factors with the greatest influence in vector distribution were slope, vegetation cover, annual mean temperature, and altitude. By using ecological niche models, it is possible to identify areas with higher probability of presence of Ph. papatasi, which guides public health policy makers for planning better vector control interventions.
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Affiliation(s)
- Aioub Sofizadeh
- Ph.D student in Medical Entomology and Vector Control, International Campus, Tehran University of Medical Sciences, Tehran, Iran
| | - Yavar Rassi
- Department of Medical Entomology and Vector Control, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran (; ; ; )
| | - Hassan Vatandoost
- Department of Medical Entomology and Vector Control, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran (; ; ; )
| | - Ahmad Ali Hanafi-Bojd
- Department of Medical Entomology and Vector Control, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran (; ; ; )
| | | | | | - Amir Ahmad Akhavan
- Department of Medical Entomology and Vector Control, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran (; ; ; )
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Shirzadi MR, Mollalo A, Yaghoobi-Ershadi MR. Dynamic Relations between Incidence of Zoonotic Cutaneous Leishmaniasis and Climatic Factors in Golestan Province, Iran. J Arthropod Borne Dis 2015; 9:148-60. [PMID: 26623427 PMCID: PMC4662787] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2014] [Accepted: 10/01/2014] [Indexed: 11/29/2022] Open
Abstract
BACKGROUND Zoonotic Cutaneous Leishmaniasis (ZCL), an important public health problem in Iran, is sensitive to climate conditions. This study aimed to examine dynamic relations between the climate factors and incidence of ZCL in Golestan Province, northern Iran during 2010-2012. METHODS Data of monthly climatic factors, including temperature variables, relative humidity variables, evaporation, total rainfall, and number of freezing and rainy days together with monthly ZCL incidence were used. Spear-man rank correlation was carried out to explain associations between the monthly ZCL incidence rate and climate factors at 0, 1, 2, 3 and 4 months lagged periods. Pearson's correlation analysis was conducted to examine the type and strength of relationships between the spatially averaged climate factors and ZCL incidence rate in district level. Stepwise multiple regression was used to find the best combination of independent climatic variables, which predict the ZCL incidence. RESULTS Spearman correlation analysis indicated that the highest correlations between climate factors and monthly ZCL incidence were established when the climate time-series lagged the ZCL incidence series, especially two month prior to disease incidence. Based on the results of the both Spearman rank correlation and Pearson correlation analyses, ZCL incidences in Golestan Province tend to be more prevalent in areas with higher temperature, lower relative humidity, lower total rainfall, higher evaporation and lower number of rainy days. The results of stepwise regression analysis indicated that minimum temperature, mean humidity, and rainfall had considerable effect on ZCL incidence. CONCLUSION Climate factors are major determinants of ZCL incidence rate in Golestan Province and such climate conditions provide favourable conditions for propagation and transmission of ZCL in this endemic area.
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Affiliation(s)
- Mohammad Reza Shirzadi
- Communicable Diseases Management Center, Ministry of Health and Medical Education, Tehran, Iran
| | - Abolfazl Mollalo
- Department of Geo-spatial Information System (GIS), Center of Excellence in GIS, K. N. Toosi University of Technology, Tehran, Iran,Corresponding author: Mr Abolfazl Mollalo,
| | - Mohammad Reza Yaghoobi-Ershadi
- Department of Medical Entomology and Vector Control, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran
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Mollalo A, Alimohammadi A, Khoshabi M. Spatial and spatio-temporal analysis of human brucellosis in Iran. Trans R Soc Trop Med Hyg 2014; 108:721-8. [DOI: 10.1093/trstmh/tru133] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/08/2023] Open
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Mollalo A, Alimohammadi A, Shahrisvand M, Reza Shirzadi M, Reza Malek M. Spatial and statistical analyses of the relations between vegetation cover and incidence of cutaneous leishmaniasis in an endemic province, northeast of Iran. Asian Pacific Journal of Tropical Disease 2014. [DOI: 10.1016/s2222-1808(14)60500-4] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/25/2022]
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32
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Mollalo A, Alimohammadi A, Shirzadi MR, Malek MR. Geographic information system-based analysis of the spatial and spatio-temporal distribution of zoonotic cutaneous leishmaniasis in Golestan Province, north-east of Iran. Zoonoses Public Health 2014; 62:18-28. [PMID: 24628913 DOI: 10.1111/zph.12109] [Citation(s) in RCA: 26] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2013] [Indexed: 11/27/2022]
Abstract
Zoonotic cutaneous leishmaniasis (ZCL), a vector-borne disease, poses serious psychological as well as social and economic burden to many rural areas of Iran. The main objectives of this study were to analyse yearly spatial distribution and the possible spatial and spatio-temporal clusters of the disease to better understand spatio-temporal epidemiological aspects of ZCL in rural areas of an endemic province, located in north-east of Iran. Cross-sectional survey was performed on 2983 recorded cases during the period of 2010-2012 at village level throughout the study area. Global clustering methods including the average nearest-neighbour distance, Moran's I, general G indices and Ripley's K-function were applied to investigate the annual spatial distribution of the existing point patterns. Presence of spatial and spatio-temporal clusters was investigated using the spatial and space-time scan statistics. For each year, semivariogram analysis and all global clustering methods indicated meaningful persistent spatial autocorrelation and highly clustered distribution of ZCL, respectively. Eight significant spatial clusters, mainly located in north and northeast of the province, and one space-time cluster, observed in northern part of the province and during the period of September 2010-November 2010, were detected. Comparison of the location of ZCL clusters with environmental conditions of the study area showed that 97.8% of cases in clusters were located at low altitudes below 725 m above sea level with predominantly arid and semi-arid climates and poor socio-economic conditions. The identified clusters highlight high-risk areas requiring special plans and resources for more close monitoring and control of the disease.
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Affiliation(s)
- A Mollalo
- Department of Geo-spatial Information System (GIS), Center of Excellence in GIS, K. N. Toosi University of Technology, Tehran, Iran
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