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1.
Front Public Health ; 9: 743558, 2021.
Article in English | MEDLINE | ID: covidwho-1775906

ABSTRACT

Background: As the first domestic PD-1 antibody approved for lung cancer in China, camrelizumab has exhibited proven effectiveness for non-small-cell lung cancer (NSCLC) patients. However, the cost-effectiveness of this new regimen remains to be investigated. Objective: To evaluate the cost-effectiveness of camrelizumab combination therapy vs. chemotherapy for previously untreated patients with advanced, non-squamous NSCLC without Alk or Egfr genomic aberrations from the perspective of China's healthcare system. Methods: Based on the CameL trial, the study developed a three-health state Markov model to evaluate the cost-effectiveness of adding camrelizumab to chemotherapy compared to chemotherapy alone in NSCLC patients. The analysis models were conducted for patients unselected by PD-L1 tumor expression (the base case) and the patient subgroup with PD-L1-expressing tumors (≥1%). Primary model outcomes included the costs in US dollars and health outcomes in quality-adjusted life-years (QALYs) as well as the incremental cost-effectiveness ratio (ICER) under a willingness-to-pay threshold of $31,500 per QALY. Additionally, a scenario analysis that adjusted within-trial crossover was employed to evaluate camrelizumab combination therapy compared to chemotherapy without subsequent use of PD1/PD-L1 antibodies. Results: Camrelizumab combination therapy was more costly and provided additional 0.11 QALYs over chemotherapy in the base case analysis (0.86 vs. 0.75 QALYs), 0.12 QALYs over chemotherapy in the subgroup analysis (0.99 vs. 0.88 QALYs), and 0.34 QALYs over chemotherapy in the scenario analysis (0.86 vs. 0.52 QALYs). Correspondingly, the ICER was $63,080 per QALY, $46,311 per QALY, and $30,591 per QALY, in the base case, the subgroup, and the scenario analysis, respectively. One-way sensitivity analyses revealed that ICERs of the base case and the subgroup analysis were most sensitive to the cost of camrelizumab, the cost of pemetrexed. Besides, the base case and subgroup analysis were more sensitive to the risk of neutrophil count decreased in the camrelizumab and the utility of stable disease, respectively. Conclusion: Although camrelizumab combination therapy is not cost-effective as first-line therapy for NSCLC patients in China in the base case, adjusting within-trial crossover would move the treatment regimen toward cost-effectiveness in the scenario analysis.


Subject(s)
Carcinoma, Non-Small-Cell Lung , Lung Neoplasms , Antibodies, Monoclonal, Humanized , Antineoplastic Combined Chemotherapy Protocols/therapeutic use , Carcinoma, Non-Small-Cell Lung/drug therapy , Carcinoma, Non-Small-Cell Lung/pathology , Cost-Benefit Analysis , Humans , Lung Neoplasms/drug therapy , Lung Neoplasms/pathology
2.
Front Comput Neurosci ; 15: 803724, 2021.
Article in English | MEDLINE | ID: covidwho-1715022

ABSTRACT

Medical image fusion has an indispensable value in the medical field. Taking advantage of structure-preserving filter and deep learning, a structure preservation-based two-scale multimodal medical image fusion algorithm is proposed. First, we used a two-scale decomposition method to decompose source images into base layer components and detail layer components. Second, we adopted a fusion method based on the iterative joint bilateral filter to fuse the base layer components. Third, a convolutional neural network and local similarity of images are used to fuse the components of the detail layer. At the last, the final fused result is got by using two-scale image reconstruction. The contrast experiments display that our algorithm has better fusion results than the state-of-the-art medical image fusion algorithms.

3.
EuropePMC; 2020.
Preprint in English | EuropePMC | ID: ppcovidwho-325233

ABSTRACT

COVID-19 global pandemic is an unprecedented health crisis. Since the outbreak, many researchers around the world have produced an extensive collection of literatures. For the research community and the general public to digest, it is crucial to analyse the text and provide insights in a timely manner, which requires a considerable amount of computational power. Clouding computing has been widely adopted in academia and industry in recent years. In particular, hybrid cloud is gaining popularity since its two-fold benefits: utilising existing resource to save cost and using additional cloud service providers to gain assess to extra computing resources on demand. In this paper, we developed a system utilising the Aneka PaaS middleware with parallel processing and multi-cloud capability to accelerate the ETL and article categorising process using machine learning technology on a hybrid cloud. The result is then persisted for further referencing, searching and visualising. Our performance evaluation shows that the system can help with reducing processing time and achieving linear scalability. Beyond COVID-19, the application might be used directly in broader scholarly article indexing and analysing.

4.
Front Med (Lausanne) ; 8: 781781, 2021.
Article in English | MEDLINE | ID: covidwho-1566656

ABSTRACT

Background: The outbreak of novel coronavirus disease 2019 (COVID-19) has led to tremendous individuals visit medical institutions for healthcare services. Public gatherings and close contact in clinics and emergency departments may increase the exposure and cross-infection of COVID-19. Objectives: The purpose of this study was to develop and deploy an intelligent response system for COVID-19 voice consultation, to provide suggestions of response measures based on actual information of users, and screen COVID-19 suspected cases. Methods: Based on the requirements analysis of business, user, and function, the physical architecture, system architecture, and core algorithms are designed and implemented. The system operation process is designed according to guidance documents of the National Health Commission and the actual experience of prevention, diagnosis and treatment of COVID-19. Both qualitative (system construction) and quantitative (system application) data from the real-world healthcare service of the system were retrospectively collected and analyzed. Results: The system realizes the functions, such as remote deployment and operations, fast operation procedure adjustment, and multi-dimensional statistical report capability. The performance of the machine-learning model used to develop the system is better than others, with the lowest Character Error Rate (CER) 8.13%. As of September 24, 2020, the system has received 12,264 times incoming calls and provided a total of 11,788 COVID-19-related consultation services for the public. Approximately 85.2% of the users are from Henan Province and followed by Beijing (2.5%). Of all the incoming calls, China Mobile contributes the largest proportion (66%), while China Unicom and China Telecom are accounted for 23% and 11%. For the time that users access the system, there is a peak period in the morning (08:00-10:00) and afternoon (14:00-16:00), respectively. Conclusions: The intelligent response system has achieved appreciable practical implementation effects. Our findings reveal that the provision of inquiry services through an intelligent voice consultation system may play a role in optimizing the allocation of healthcare resources, improving the efficiency of medical services, saving medical expenses, and protecting vulnerable groups.

5.
BMC Nephrol ; 22(1): 381, 2021 11 13.
Article in English | MEDLINE | ID: covidwho-1515439

ABSTRACT

BACKGROUND: Kidney dysfunction occurs in severe COVID-19, and is a predictor of COVID-19 mortality. Whether kidney dysfunction causes severe COVID-19, and hence is a target of intervention, or whether it is a symptom, is unclear because conventional observational studies are open to confounding. To obtain unconfounded estimates, we used Mendelian randomization to examine the role of kidney function in severe COVID-19. METHODS: We used genome-wide significant, uncorrelated genetic variants to predict kidney function, in terms of estimated glomerular filtration rate (eGFR) and urine albumin-to-creatinine ratio (UACR), and then assessed whether people with genetically instrumented higher eGFR or lower UACR, an indication of better kidney function, had a lower risk of severe COVID-19 (8779 cases, 1,001,875 controls), using the largest available cohorts with extensive genotyping. For comprehensiveness, we also examined their role in COVID-19 hospitalization (24,274 cases, 2,061,529 controls) and all COVID-19 (1,12,612 cases, 2,474,079 controls). RESULTS: Genetically instrumented higher eGFR was associated with lower risk of severe COVID-19 (odds ratio (OR) 0.90, 95% confidence interval (CI) 0.83, 0.98) but not related to COVID-19 hospitalization or infection. Genetically instrumented UACR was not related to COVID-19. CONCLUSIONS: Kidney function appears to be one of the key targets for severe COVID-19 treatment. Use of available medications to improve kidney function, such as antihypertensives, might be beneficial for COVID-19 treatment, with relevance to drug repositioning.


Subject(s)
COVID-19/complications , COVID-19/genetics , Glomerular Filtration Rate/genetics , Kidney/physiopathology , Patient Acuity , Albuminuria/urine , Case-Control Studies , Creatinine/urine , Genetic Variation , Genome-Wide Association Study , Hospitalization , Humans , Mendelian Randomization Analysis , Risk Factors , SARS-CoV-2 , /genetics
6.
Healthcare (Basel) ; 9(11)2021 Nov 08.
Article in English | MEDLINE | ID: covidwho-1512245

ABSTRACT

Short-term and large-scale full-population virus testing is crucial in containing the spread of the COVID-19 pandemic in China. However, the uneven distribution of health service facilities in terms of space and size may lead to prolonged crowding during testing, thus increasing the chance of virus cross-infection. Therefore, appropriate control of crowd exposure time in large-scale virus testing should be an important goal in the layout of urban community health facilities. This paper uses the Quanta concept and Wells-Riley model to define the "certain-exposure time" under low cross-infection rate. Then, an agent-based simulation model was used to simulate the reasonable screening efficiency of community health service facilities during certain-exposure time at different stages of the COVID-19 pandemic and under different screening processes. Eventually, the screening efficiency was evaluated for all community health service centers in Wuhan. During the early period of the pandemic, 23.13% of communities failed to complete virus testing of community residents within 2 h of certain-exposure time, leaving approximately 56.07% of the population unscreened; during the later period of the COVID-19 pandemic, approximately 53% of communities and 75% of residents could not be screened. The results can pinpoint the distribution of community health service centers with inadequate screening capacity, facilitate targeted policymaking and planning, and effectively curb COVID-19 cross-infection during screening.

7.
BMC Infect Dis ; 21(1): 816, 2021 Aug 14.
Article in English | MEDLINE | ID: covidwho-1440911

ABSTRACT

BACKGROUND: The coronavirus disease 2019 (COVID-19) has become a pandemic. Few studies have been conducted to investigate the spatio-temporal distribution of COVID-19 on nationwide city-level in China. OBJECTIVE: To analyze and visualize the spatiotemporal distribution characteristics and clustering pattern of COVID-19 cases from 362 cities of 31 provinces, municipalities and autonomous regions in mainland China. METHODS: A spatiotemporal statistical analysis of COVID-19 cases was carried out by collecting the confirmed COVID-19 cases in mainland China from January 10, 2020 to October 5, 2020. Methods including statistical charts, hotspot analysis, spatial autocorrelation, and Poisson space-time scan statistic were conducted. RESULTS: The high incidence stage of China's COVID-19 epidemic was from January 17 to February 9, 2020 with daily increase rate greater than 7.5%. The hot spot analysis suggested that the cities including Wuhan, Huangshi, Ezhou, Xiaogan, Jingzhou, Huanggang, Xianning, and Xiantao, were the hot spots with statistical significance. Spatial autocorrelation analysis indicated a moderately correlated pattern of spatial clustering of COVID-19 cases across China in the early phase, with Moran's I statistic reaching maximum value on January 31, at 0.235 (Z = 12.344, P = 0.001), but the spatial correlation gradually decreased later and showed a discrete trend to a random distribution. Considering both space and time, 19 statistically significant clusters were identified. 63.16% of the clusters occurred from January to February. Larger clusters were located in central and southern China. The most likely cluster (RR = 845.01, P < 0.01) included 6 cities in Hubei province with Wuhan as the centre. Overall, the clusters with larger coverage were in the early stage of the epidemic, while it changed to only gather in a specific city in the later period. The pattern and scope of clusters changed and reduced over time in China. CONCLUSIONS: Spatio-temporal cluster detection plays a vital role in the exploration of epidemic evolution and early warning of disease outbreaks and recurrences. This study can provide scientific reference for the allocation of medical resources and monitoring potential rebound of the COVID-19 epidemic in China.


Subject(s)
COVID-19 , China/epidemiology , Cities/epidemiology , Humans , Pandemics , SARS-CoV-2 , Spatio-Temporal Analysis
10.
Asian J Surg ; 44(10): 1292-1293, 2021 10.
Article in English | MEDLINE | ID: covidwho-1330643
11.
Neurol Sci ; 42(7): 2645-2651, 2021 Jul.
Article in English | MEDLINE | ID: covidwho-1217442

ABSTRACT

OBJECTIVE: We aim to determine the risk of acute ischemic stroke in patients with severe and non-severe coronavirus disease 2019 (COVID-19). METHODS: A literature search was conducted in the PubMed, Embase, Web of Science, and Cochrane Library databases until October 28, 2020. Studies covering COVID-19's severity classification data and COVID-19 patients with acute ischemic stroke were included. Two independent evaluators extracted data, and the random effects model was used to calculate the risk ratios (RR) and 95% confidence interval (95% CI) of acute ischemic stroke associated with COVID-19's severity. RESULTS: A total of 8 studies were included, involving 5266 patients. Among all COVID-19 patients, the total incidence of ischemic stroke was 1.76% (95% CI: 0.82-3.01). Severe patients have an increased risk of acute ischemic stroke compared with non-severe patients (RR = 3.53, 95% CI: 2.06-6.07, P < 0.0001; I2 = 12%). This association was also observed when COVID-19's severity was defined by clinical parameters (RR 2.91, 95% CI: 1.17-7.26, P = 0.02; I2 = 29%) and the need for intensive care (RR 4.47, 95% CI: 2.40-8.31, P < 0.0001; I2 = 0%). CONCLUSIONS: This meta-analysis shows that the severe course of COVID-19 is associated with an increased risk of acute ischemic stroke.


Subject(s)
Brain Ischemia , COVID-19 , Ischemic Stroke , Stroke , Brain Ischemia/complications , Brain Ischemia/epidemiology , Humans , SARS-CoV-2 , Stroke/epidemiology
12.
BMC Med ; 19(1): 72, 2021 03 24.
Article in English | MEDLINE | ID: covidwho-1148216

ABSTRACT

BACKGROUND: Observational studies suggest poorer glycemic traits and type 2 diabetes associated with coronavirus disease 2019 (COVID-19) risk although these findings could be confounded by socioeconomic position. We conducted a two-sample Mendelian randomization to clarify their role in COVID-19 risk and specific COVID-19 phenotypes (hospitalized and severe cases). METHOD: We identified genetic instruments for fasting glucose (n = 133,010), 2 h glucose (n = 42,854), glycated hemoglobin (n = 123,665), and type 2 diabetes (74,124 cases and 824,006 controls) from genome wide association studies and applied them to COVID-19 Host Genetics Initiative summary statistics (17,965 COVID-19 cases and 1,370,547 population controls). We used inverse variance weighting to obtain the causal estimates of glycemic traits and genetic predisposition to type 2 diabetes in COVID-19 risk. Sensitivity analyses included MR-Egger and weighted median method. RESULTS: We found genetic predisposition to type 2 diabetes was not associated with any COVID-19 phenotype (OR: 1.00 per unit increase in log odds of having diabetes, 95%CI 0.97 to 1.04 for overall COVID-19; OR: 1.02, 95%CI 0.95 to 1.09 for hospitalized COVID-19; and OR: 1.00, 95%CI 0.93 to 1.08 for severe COVID-19). There were no strong evidence for an association of glycemic traits in COVID-19 phenotypes, apart from a potential inverse association for fasting glucose albeit with wide confidence interval. CONCLUSION: We provide some genetic evidence that poorer glycemic traits and predisposition to type 2 diabetes unlikely increase the risk of COVID-19. Although our study did not indicate glycemic traits increase severity of COVID-19, additional studies are needed to verify our findings.


Subject(s)
Blood Glucose/genetics , COVID-19/genetics , Diabetes Mellitus, Type 2/genetics , Glycated Hemoglobin A/genetics , Mendelian Randomization Analysis , Adult , Blood Glucose/metabolism , COVID-19/blood , COVID-19/epidemiology , COVID-19/pathology , Case-Control Studies , Critical Illness/epidemiology , Diabetes Mellitus, Type 2/blood , Diabetes Mellitus, Type 2/complications , Diabetes Mellitus, Type 2/epidemiology , Fasting/blood , Female , Genetic Predisposition to Disease , Genome-Wide Association Study , Glycated Hemoglobin A/metabolism , Humans , Male , Phenotype , Polymorphism, Single Nucleotide , Risk Factors , SARS-CoV-2/pathogenicity , Severity of Illness Index
13.
Angewandte Chemie ; n/a(n/a), 2021.
Article in English | Wiley | ID: covidwho-1135068

ABSTRACT

SARS-CoV-2 attaches to its host receptor, angiotensin-converting enzyme 2 (ACE2), via the receptor-binding domain (RBD) of the spike protein. The RBD glycoprotein is a critical target for the development of neutralizing antibodies and vaccines against SARS-CoV-2. However, the high heterogeneity of RBD glycoforms may lead to an incomplete neutralization effect and impact the immunogenic integrity of RBD-based vaccines. Investigating the role of different carbohydrate domains is of paramount importance. Unfortunately, there is no viable method for preparing RBD glycoproteins with structurally defined glycans. Herein we describe a highly efficient and scalable strategy for the preparation of six glycosylated RBDs bearing defined structure glycoforms at T323, N331 and N343. A combination of modern oligosaccharide, peptide synthesis and recombinant protein engineering provides a robust route to deciphering carbohydrate structure?function relationships.

14.
Results Phys ; 22: 103829, 2021 Mar.
Article in English | MEDLINE | ID: covidwho-1046140

ABSTRACT

This study was to explore the performance of immune function and compositions of hospitalization cost for patients with COVID-19 as well as the application of a grey relational mathematical model (GRMM). A total of 100 COVID-19 patients diagnosed by nucleic acid test and chest CT examination in our hospital were collected in this study. They were divided into 2 groups: non-severe group (mild and moderate patients, n = 57 cases), and severe group (severe and critical patients, n = 43 cases) based on the Diagnosis and Treatment Protocol for Novel Coronavirus Pneumonia (Trial Version 7) published by the World Health Organization (WHO). The general clinical data, blood routine indexes, cellular immune and humoral immune function test indexes, and the composition of hospitalization costs of the two groups of patients were collected and analyzed. The results showed that the average age, proportion of males, smoking history, and the number and proportion of patients in the non-severe group were smaller than those in the severe group (P < 0.05); the severe group had significantly more shortness of breath patients than the non-severe group (P < 0.05). Compared with the non-severe group, the number of white blood cells (WBC), the number and proportion of neutrophils, and the count of neutrophils/lymphocytes in the severe group increased obviously (P < 0.05), and the number of lymphocytes and the proportion of monocytes decreased dramatically (P < 0.05); the number and proportion of CD3+, CD4+, CD8+, and CD19+ in the severe group were much lower in contrast to those in the non-severe group (P < 0.05), while the ratio of CD4+/CD8+ was greatly higher in contrast to that of non-severe patients (P < 0.05). Compared with the non-severe group, the bed fee, laboratory test fee, diagnosis fee, and medicine fee of the severe group were increased observably (P < 0.05). The changes in hospitalization cost of patients in the severe group was related to bed fees, laboratory fees, and expenses of proprietary Chinese medicines, while the hospitalization cost of patients in the severe group was related to bed fees, laboratory fees, and examination fees. The results revealed that elderly COVID-19 patients with basic diseases were prone to develop severe disease, immune cell depletion may be one of the reasons for the development of severe patients, and the medical insurance policy greatly reduced the hospitalization costs of COVID-19 patients.

16.
Front Microbiol ; 11: 580137, 2020.
Article in English | MEDLINE | ID: covidwho-883855

ABSTRACT

The coronavirus disease 19 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has become a global pandemic since the first report in Wuhan. COVID-19 is a zoonotic disease and the natural reservoir of SARS-CoV-2 seems to be bats. However, the intermediate host explaining the transmission and evolvement is still unclear. In addition to the wildlife which has access to contact with bats in the natural ecological environment and then infects humans in wildlife market, domestic animals are also able to establish themselves as the intermediate host after infected by SARS-CoV-2. Although recent studies related to SARS-CoV-2 have made a lot of progress, many critical issues are still unaddressed. Here, we reviewed findings regarding the investigations of the intermediate host, which may inspire future investigators and provide them with plenty of information. The results demonstrate the critical role of the intermediate host in the transmission chain of SARS-CoV-2, and the efficient intervention on this basis may be useful to prevent further deterioration of COVID-19.

17.
Br J Clin Pharmacol ; 87(4): 1839-1846, 2021 04.
Article in English | MEDLINE | ID: covidwho-835295

ABSTRACT

AIM: Angiotensin-converting enzyme 2 (ACE 2) is the binding domain for severe acute respiratory syndrome coronavirus (SARS-CoV) and SARSCoV-2. Some antihypertensive drugs affect ACE2 expression or activity (ACE inhibitors and angiotensin II receptor blockers [ARBs]), suggesting use of other hypertensives might be preferable, such as calcium channel blockers (CCBs). Given the limited evidence, the International Society of Hypertension does not support such a policy. METHODS: We used a Mendelian randomization study to obtain unconfounded associations of antihypertensives, instrumented by published genetic variants in genes regulating target proteins of these drugs, with immune (lymphocyte and neutrophil percentage) and inflammatory (tumour necrosis factor alpha [TNF-α]) markers in the largest available genome-wide association studies. RESULTS: Genetically predicted effects of ACE inhibitors increased lymphocyte percentage (0.78, 95% confidence interval [CI] 0.35, 1.22), decreased neutrophil percentage (-0.64, 95% CI -1.09, -0.20) and possibly lowered TNF-α (-4.92, 95% CI -8.50, -1.33). CCBs showed a similar pattern for immune function (lymphocyte percentage 0.21, 95% CI 0.05 to 0.36; neutrophil percentage -0.23, 95% CI -0.39 to -0.08) but had no effect on TNF-α, as did potassium-sparing diuretics and aldosterone antagonists, and vasodilator antihypertensives. ARBs and other classes of hypertensives had no effect on immune function or TNF-α. CONCLUSION: Varying effects of different classes of antihypertensives on immune and inflammatory markers do not suggest antihypertensive use based on their role in ACE2 expression, but instead suggest investigation of the role of antihypertensives in immune function and inflammation might reveal important information that could optimize their use in SARSCoV-2.


Subject(s)
Angiotensin-Converting Enzyme 2/metabolism , Angiotensin-Converting Enzyme Inhibitors/therapeutic use , Antihypertensive Agents/therapeutic use , Hypertension/drug therapy , Immunity/drug effects , Inflammation/drug therapy , Polymorphism, Single Nucleotide , Angiotensin-Converting Enzyme Inhibitors/adverse effects , Antihypertensive Agents/adverse effects , Genome-Wide Association Study , Humans , Hypertension/enzymology , Hypertension/genetics , Immunity/genetics , Inflammation/enzymology , Inflammation/immunology , Lymphocytes/drug effects , Lymphocytes/immunology , Lymphocytes/metabolism , Mendelian Randomization Analysis , Neutrophils/drug effects , Neutrophils/immunology , Neutrophils/metabolism , Tumor Necrosis Factor-alpha/metabolism
18.
SSRN; 2020.
Preprint | SSRN | ID: ppcovidwho-719

ABSTRACT

Background: Since the coronavirus disease 2019 (COVID-19) outbreak in Wuhan in late 2019, China has been implementing an unprecedented quarantine strategy cover

19.
Zhong Nan Da Xue Xue Bao Yi Xue Ban ; 45(5): 582-590, 2020 May 28.
Article in English, Chinese | MEDLINE | ID: covidwho-745318

ABSTRACT

OBJECTIVES: To analyze the regional epidemic features of coronavirus disease 2019 (COVID-19) in Henan Province, China. METHODS: According to the data of COVID-19 patients and the resident population at the end of 2018 in Henan Province, statistical description and analysis of epidemiological characteristics of COVID-19 in Henan Province were conducted, including the time distribution, population distribution, and regional distribution. RESULTS: The cumulative incidence of COVID-19 in Henan Province was 1.32/100 000, the cure rate was 98.03%, and the fatality rate was 1.73% by March 9, 2020. The incidence curve showed that the epidemic peak reached from January 24 to January 28. The high-incidence area was Xinyang, with a standardized cumulative incidence rate of 4.36/100 000. There were 580 female COVID-19 patients (45.60%), 688 males (54.09%) in Henan Province. The incidence of males was 1.41/100 000, while the incidence of females was 1.23/100 000. The age with the highest incidence of COVID-19 in Henan Province was 20-69 years old (88.68%). The incidence rate was highest in men aged 30-39 (2.51/ 100 000), while the lowest rate in women aged 0-9 (0.16/100 000). There were 1 225 local patients (96.31%), and the rural patients (45.73%) were slightly higher than the urban patients (44.02%) in Henan Province. A total of 63.60% patients had traveled or lived in Hubei or contacted with people who came from Hubei to Henan. The proportion of patients whose family members suffered from COVID-19 was 32.70%. Global spatial autocorrelation analysis suggested that there was a statistically significant positive correlation in the spatial distribution of COVID-19 patients in Henan Province (Moran's I=0.248, Z=2.955, P<0.01). CONCLUSIONS: There are differences in the morbidity and mortality of COVID-19 patients in different areas of Henan Province, with epidemic peak reaching from January 24 to January 28. Henan is dominated by local patients, male patients, and patients with contact history in Hubei. The space appears to be moderately clustered.


Subject(s)
Coronavirus Infections/epidemiology , Pneumonia, Viral/epidemiology , Adult , Aged , Betacoronavirus , COVID-19 , Child , Child, Preschool , China/epidemiology , Female , Humans , Incidence , Infant , Infant, Newborn , Male , Middle Aged , Pandemics , SARS-CoV-2 , Spatial Analysis , Young Adult
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