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Pathogens and Global Health Oct 2023Previous studies suggest that the risk of human infection by hantavirus, a family of rodent-borne viruses, might be affected by different environmental determinants such... (Review)
Review
Previous studies suggest that the risk of human infection by hantavirus, a family of rodent-borne viruses, might be affected by different environmental determinants such as land cover, land use and land use change. This study examined the association between land-cover, land-use, land use change, and human hantavirus infection risk. PubMed and Scopus databases were interrogated using terms relative to land use (change) and human hantavirus disease. Screening and selection of the articles were completed by three independent reviewers. Classes of land use assessed by the different studies were categorized into three macro-categories of exposure ('Agriculture', 'Forest Cover', 'Urban Areas') to qualitatively synthesize the direction of the association between exposure variables and hantavirus infection risk in humans. A total of 25 articles were included, with 14 studies (56%) conducted in China, 4 studies (16%) conducted in South America and 7 studies (28%) conducted in Europe. Most of the studies (88%) evaluated land cover or land use, while 3 studies (12%) evaluated land use change, all in relation to hantavirus infection risk. We observed that land cover and land-use categories could affect hantavirus infection incidence. Overall, agricultural land use was positively associated with increased human hantavirus infection risk, particularly in China and Brazil. In Europe, a positive association between forest cover and hantavirus infection incidence was observed. Studies that assessed the relationship between built-up areas and hantavirus infection risk were more variable, with studies reporting positive, negative or no associations.
PubMed: 37876214
DOI: 10.1080/20477724.2023.2272097 -
Expert Review of Pharmacoeconomics &... Jan 2024The increasing availability of data and computing power has made machine learning (ML) a viable approach to faster, more efficient healthcare delivery. (Review)
Review
INTRODUCTION
The increasing availability of data and computing power has made machine learning (ML) a viable approach to faster, more efficient healthcare delivery.
METHODS
A systematic literature review (SLR) of published SLRs evaluating ML applications in healthcare settings published between1 January 2010 and 27 March 2023 was conducted.
RESULTS
In total 220 SLRs covering 10,462 ML algorithms were reviewed. The main application of AI in medicine related to the clinical prediction and disease prognosis in oncology and neurology with the use of imaging data. Accuracy, specificity, and sensitivity were provided in 56%, 28%, and 25% SLRs respectively. Internal and external validation was reported in 53% and less than 1% of the cases respectively. The most common modeling approach was neural networks (2,454 ML algorithms), followed by support vector machine and random forest/decision trees (1,578 and 1,522 ML algorithms, respectively).
EXPERT OPINION
The review indicated considerable reporting gaps in terms of the ML's performance, both internal and external validation. Greater accessibility to healthcare data for developers can ensure the faster adoption of ML algorithms into clinical practice.
Topics: Algorithms; Machine Learning; Medical Oncology; Neural Networks, Computer
PubMed: 37955147
DOI: 10.1080/14737167.2023.2279107 -
International Journal of Medical... Aug 2023Acute respiratory diseases are a leading cause of morbidity and mortality in children. Cough is a common symptom of acute respiratory diseases and the sound of cough can... (Review)
Review
BACKGROUND
Acute respiratory diseases are a leading cause of morbidity and mortality in children. Cough is a common symptom of acute respiratory diseases and the sound of cough can be indicative of the respiratory disease. However, cough sound assessment in routine clinical practice is limited to human perception and the skills of the clinician. Objective cough sound evaluation has the potential to aid clinicians in acute respiratory disease diagnosis. In this systematic review, we assess and summarize the predictive ability of machine learning algorithms in analyzing cough sounds of acute respiratory diseases in the pediatric population.
METHOD
Our systematic search of the Scopus, Medline, and Embase databases on 25 January 2023 identified six articles meeting the inclusion criteria. Quality assessment of the included studies was performed using the checklist for the assessment of medical artificial intelligence.
RESULTS
Our analysis shows variability in the input to the machine learning algorithms, such as the use of various cough sound features and combining cough sound features with clinical features. The use of the machine learning algorithms also varies from conventional algorithms, such as logistic regression and support vector machine, to deep learning techniques, such as convolutional neural networks. The classification accuracy for the detection of bronchiolitis, croup, pertussis, and pneumonia across five articles is in the range of 82-96%. However, a significant drop is observed in the detection accuracy for bronchiolitis and pneumonia in the remaining article.
CONCLUSION
The number of articles is limited but, in general, the predictive ability of cough sound classification algorithms in childhood acute respiratory diseases shows promise.
Topics: Child; Humans; Cough; Artificial Intelligence; Algorithms; Pneumonia; Bronchiolitis; Machine Learning
PubMed: 37224643
DOI: 10.1016/j.ijmedinf.2023.105093 -
Parasites & Vectors Aug 2023Bovine babesiosis, caused by different Babesia spp. such as B. bovis, B. bigemina, B. divergens, and B. major, is a global disease that poses a serious threat to... (Review)
Review
Bovine babesiosis, caused by different Babesia spp. such as B. bovis, B. bigemina, B. divergens, and B. major, is a global disease that poses a serious threat to livestock production. Babesia bovis infections are associated with severe disease and increased mortality in adult cattle, making it the most virulent agent of bovine babesiosis. Babesia bovis parasites undergo asexual reproduction within bovine red blood cells, followed by sexual reproduction within their tick vectors, which transmit the parasite transovarially. Current control methods, including therapeutic drugs (i.e., imidocarb) have been found to lead to drug resistance. Moreover, changing environmental factors add complexity to efficient parasite control. Understanding the fundamental biology, host immune responses, and host-parasite interactions of Babesia parasites is critical for developing next-generation vaccines to control acute disease and parasite transmission. This systematic review analyzed available research papers on vaccine development and the associated immune responses to B. bovis. We compiled and consolidated the reported vaccine strategies, considering the study design and rationale of each study, to provide a systematic review of knowledge and insights for further research. Thirteen studies published since 2014 (inclusive) represented various vaccine strategies developed against B. bovis such as subunit, live attenuated, and viral vector vaccines. Such strategies incorporated B. bovis proteins or whole live parasites with the latter providing the most effective prophylaxis against bovine babesiosis. Incorporating novel research approaches, such as "omics" will enhance our understanding of parasite vulnerabilities.
Topics: Animals; Cattle; Babesia bovis; Babesiosis; Cattle Diseases; Babesia; Vaccines
PubMed: 37563668
DOI: 10.1186/s13071-023-05885-z -
The Cochrane Database of Systematic... Apr 2024Dengue is a global health problem of high significance, with 3.9 billion people at risk of infection. The geographic expansion of dengue virus (DENV) infection has... (Review)
Review
BACKGROUND
Dengue is a global health problem of high significance, with 3.9 billion people at risk of infection. The geographic expansion of dengue virus (DENV) infection has resulted in increased frequency and severity of the disease, and the number of deaths has increased in recent years. Wolbachia,an intracellular bacterial endosymbiont, has been under investigation for several years as a novel dengue-control strategy. Some dengue vectors (Aedes mosquitoes) can be transinfected with specific strains of Wolbachia, which decreases their fitness (ability to survive and mate) and their ability to reproduce, inhibiting the replication of dengue. Both laboratory and field studies have demonstrated the potential effect of Wolbachia deployments on reducing dengue transmission, and modelling studies have suggested that this may be a self-sustaining strategy for dengue prevention, although long-term effects are yet to be elucidated.
OBJECTIVES
To assess the efficacy of Wolbachia-carrying Aedes speciesdeployments (specifically wMel-, wMelPop-, and wAlbB- strains of Wolbachia) for preventing dengue virus infection.
SEARCH METHODS
We searched CENTRAL, MEDLINE, Embase, four other databases, and two trial registries up to 24 January 2024.
SELECTION CRITERIA
Randomized controlled trials (RCTs), including cluster-randomized controlled trials (cRCTs), conducted in dengue endemic or epidemic-prone settings were eligible. We sought studies that investigated the impact of Wolbachia-carrying Aedes deployments on epidemiological or entomological dengue-related outcomes, utilizing either the population replacement or population suppression strategy.
DATA COLLECTION AND ANALYSIS
Two review authors independently selected eligible studies, extracted data, and assessed the risk of bias using the Cochrane RoB 2 tool. We used odds ratios (OR) with the corresponding 95% confidence intervals (CI) as the effect measure for dichotomous outcomes. For count/rate outcomes, we planned to use the rate ratio with 95% CI as the effect measure. We used adjusted measures of effect for cRCTs. We assessed the certainty of evidence using GRADE.
MAIN RESULTS
One completed cRCT met our inclusion criteria, and we identified two further ongoing cRCTs. The included trial was conducted in an urban setting in Yogyakarta, Indonesia. It utilized a nested test-negative study design, whereby all participants aged three to 45 years who presented at healthcare centres with a fever were enrolled in the study provided they had resided in the study area for the previous 10 nights. The trial showed that wMel-Wolbachia infected Ae aegypti deployments probably reduce the odds of contracting virologically confirmed dengue by 77% (OR 0.23, 95% CI 0.15 to 0.35; 1 trial, 6306 participants; moderate-certainty evidence). The cluster-level prevalence of wMel Wolbachia-carrying mosquitoes remained high over two years in the intervention arm of the trial, reported as 95.8% (interquartile range 91.5 to 97.8) across 27 months in clusters receiving wMel-Wolbachia Ae aegypti deployments, but there were no reliable comparative data for this outcome. Other primary outcomes were the incidence of virologically confirmed dengue, the prevalence of dengue ribonucleic acid in the mosquito population, and mosquito density, but there were no data for these outcomes. Additionally, there were no data on adverse events.
AUTHORS' CONCLUSIONS
The included trial demonstrates the potential significant impact of wMel-Wolbachia-carrying Ae aegypti mosquitoes on preventing dengue infection in an endemic setting, and supports evidence reported in non-randomized and uncontrolled studies. Further trials across a greater diversity of settings are required to confirm whether these findings apply to other locations and country settings, and greater reporting of acceptability and cost are important.
Topics: Animals; Humans; Aedes; Wolbachia; Dengue Virus; Mosquito Vectors; Dengue
PubMed: 38597256
DOI: 10.1002/14651858.CD015636.pub2 -
Cureus Nov 2023The use of artificial intelligence in the field of medicine - including spine surgery - is now widespread and prominent. Kyphosis is a prevalent disease in spine surgery... (Review)
Review
The use of artificial intelligence in the field of medicine - including spine surgery - is now widespread and prominent. Kyphosis is a prevalent disease in spine surgery with abundant morbidity. Predicting the development of kyphosis disease has been somewhat difficult, and the use of AI to aid in the prediction of kyphosis disease may yield new opportunities for spine surgeons. The aim of this review is to recognize the contributions of AI in predicting the development of kyphosis. Five databases/registers were searched to identify suitable records for this review. Nine studies were included in this review. The studies demonstrated that AI could be utilized to predict the development of kyphosis disease after corrective surgery for a variety of spinal pathologies, including thoracolumbar burst fracture, cervical deformity, previous kyphosis disease, and adult degenerative scoliosis. The studies utilized a variety of AI modalities, including support vector machines, decision trees, random forests, and artificial neural networks. Two of the included studies also compared the use of different AI modalities in predicting the development of kyphosis disease. The literature has demonstrated that AI can be utilized effectively to predict the development of kyphosis disease. However, the current research is limited and only sparsely covers this broad field. Therefore, we suggest that further research is needed to explore the uncharted opportunities in predicting the development of kyphosis disease. Also, further research would confirm and consolidate the benefits demonstrated by the literature included in this review.
PubMed: 38060748
DOI: 10.7759/cureus.48341 -
Experimental Biology and Medicine... Oct 2023Dengue fever disease (DFD) which is caused by four antigenically distinct dengue viruses (DENV) presents a global health threat, with tropical and subtropical regions at...
Dengue fever disease (DFD) which is caused by four antigenically distinct dengue viruses (DENV) presents a global health threat, with tropical and subtropical regions at a greater risk. The paucity of epidemiological data on dengue in West African subregion endangers efforts geared toward disease control and prevention. A systematic search of DFD prevalence, incidence, and DENV-infected in West Africa was conducted in PubMed, Scopus, African Index Medicus, and Google Scholar in line with the Preferred Reporting Items for Systematic reviews and Meta-analyses (PRISMA) guidelines. A total of 58 human prevalence studies involving 35,748 people from 8 countries were identified. Two incidence and six DENV-infected studies were also reviewed. Nigeria and Burkina Faso contributed the majority of the prevalence studies which spanned between 1968 and 2018, with a considerable variation in coverage among the countries reviewed in this study. An average prevalence of 20.97% was observed across both general prevalence and acute DENV infection study categories, ranging between 0.02% and 93%. The majority of these studies were conducted in acute febrile patients with a prevalence range of 0.02-93% while 19% ( = 11) of all studies were general population-based studies and reported a prevalence range of 17.2-75.8%. DENV-infected were reported in four out of the five countries with published reports; with DENV-2 found circulating in Cape Verde, Senegal, and Burkina Faso while DENV-3 and DENV-4 were also reported in Senegal and Cape Verde, respectively. High prevalence of DFD in human populations and the occurrence of DENV-infected have been reported in West Africa, even though weaknesses in study design were identified. Epidemiological data from most countries and population in the subregion were scarce or non-existent. This study highlights the epidemic risk of DFD in West Africa, and the need for research and surveillance to be prioritized to fill the data gap required to enact effective control measures.
Topics: Animals; Humans; Aedes; Burkina Faso; Cross-Sectional Studies; Dengue; Dengue Virus
PubMed: 37452719
DOI: 10.1177/15353702231181356 -
Viruses Jul 2023The spread of lumpy skin disease (LSD) to free countries over the last 10 years, particularly countries in Europe, Central and South East Asia, has highlighted the... (Review)
Review
The spread of lumpy skin disease (LSD) to free countries over the last 10 years, particularly countries in Europe, Central and South East Asia, has highlighted the threat of emergence in new areas or re-emergence in countries that achieved eradication. This review aimed to identify studies on LSD epidemiology. A focus was made on hosts, modes of transmission and spread, risks of outbreaks and emergence in new areas. In order to summarize the research progress regarding the epidemiological characteristics of LSD virus over the last 40 years, the Preferred Reporting Items for Systematic reviews and Meta-Analyses statement guidelines were followed, via two databases, i.e., PubMed (biomedical literature) and Scopus (peer-reviewed literature including scientific journals, books, and conference proceedings). A total of 86 scientific articles were considered and classified according to the type of epidemiological study, i.e., experimental versus observational. The main findings and limitations of the retrieved articles were summarized: buffaloes are the main non-cattle hosts, the main transmission mode is mechanical, i.e., via blood-sucking vectors, and stable flies are the most competent vectors. Vectors are mainly responsible for a short-distance spread, while cattle trade spread the virus over long distances. Furthermore, vaccine-recombinant strains have emerged. In conclusion, controlling animal trade and insects in animal transport trucks are the most appropriate measures to limit or prevent LSD (re)emergence.
Topics: Animals; Cattle; Lumpy Skin Disease; Disease Outbreaks; Bison; Books; Buffaloes
PubMed: 37631965
DOI: 10.3390/v15081622 -
Mathematical Biosciences Jul 2024Diverse modelling techniques in cholera epidemiology have been developed and used to (1) study its transmission dynamics, (2) predict and manage cholera outbreaks, and... (Review)
Review
Diverse modelling techniques in cholera epidemiology have been developed and used to (1) study its transmission dynamics, (2) predict and manage cholera outbreaks, and (3) assess the impact of various control and mitigation measures. In this study, we carry out a critical and systematic review of various approaches used for modelling the dynamics of cholera. Also, we discuss the strengths and weaknesses of each modelling approach. A systematic search of articles was conducted in Google Scholar, PubMed, Science Direct, and Taylor & Francis. Eligible studies were those concerned with the dynamics of cholera excluding studies focused on models for cholera transmission in animals, socio-economic factors, and genetic & molecular related studies. A total of 476 peer-reviewed articles met the inclusion criteria, with about 40% (32%) of the studies carried out in Asia (Africa). About 52%, 21%, and 9%, of the studies, were based on compartmental (e.g., SIRB), statistical (time series and regression), and spatial (spatiotemporal clustering) models, respectively, while the rest of the analysed studies used other modelling approaches such as network, machine learning and artificial intelligence, Bayesian, and agent-based approaches. Cholera modelling studies that incorporate vector/housefly transmission of the pathogen are scarce and a small portion of researchers (3.99%) considers the estimation of key epidemiological parameters. Vaccination only platform was utilized as a control measure in more than half (58%) of the studies. Research productivity in cholera epidemiological modelling studies have increased in recent years, but authors used diverse range of models. Future models should consider incorporating vector/housefly transmission of the pathogen and on the estimation of key epidemiological parameters for the transmission of cholera dynamics.
Topics: Cholera; Humans; Epidemiological Models; Disease Outbreaks
PubMed: 38777029
DOI: 10.1016/j.mbs.2024.109210 -
Pest Management Science Oct 2023Southern rice black-streaked dwarf virus (SRBSDV) is one of the most damaging rice viruses. The virus decreases rice quality and yield, and poses a serious threat to... (Review)
Review
Southern rice black-streaked dwarf virus (SRBSDV) is one of the most damaging rice viruses. The virus decreases rice quality and yield, and poses a serious threat to food security. From this perspective, this review performed a survey of published studies in recent years to understand the current status of SRBSDV and white-backed planthopper (WBPH, Sogatella furcifera) transmission processes in rice. Recent studies have shown that the interactions between viral virulence proteins and rice susceptibility factors shape the transmission of SRBSDV. Moreover, the transmission of SRBSDV is influenced by the interactions between viral virulence proteins and S. furcifera susceptibility factors. This review focused on the molecular mechanisms of key genes or proteins associated with SRBSDV infection in rice via the S. furcifera vector, and the host defense response mechanisms against viral infection. A sustainable control strategy using RNAi was summarized to address this pest. Finally, we also present a model for screening anti-SRBSDV inhibitors using viral proteins as targets. © 2023 Society of Chemical Industry.
Topics: Animals; Insect Vectors; Oryza; Reoviridae; Hemiptera; Plant Diseases
PubMed: 37291065
DOI: 10.1002/ps.7605