Monkeypox: balancing response and future preparedness during a global public health emergency
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Cited by 3 publications
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Spatiotemporal Epidemiological Trends of Mpox in Mainland China: Spatiotemporal Ecological Comparison Study
Background The World Health Organization declared mpox an international public health emergency. Since January 1, 2022, China has been ranked among the top 10 countries most affected by the mpox outbreak globally. However, there is a lack of spatial epidemiological studies on mpox, which are crucial for accurately mapping the spatial distribution and clustering of the disease. Objective This study aims to provide geographically accurate visual evidence to determine priority areas for mpox prevention and control. Methods Locally confirmed mpox cases were collected between June and November 2023 from 31 provinces of mainland China excluding Taiwan, Macao, and Hong Kong. Spatiotemporal epidemiological analyses, including spatial autocorrelation and regression analyses, were conducted to identify the spatiotemporal characteristics and clustering patterns of mpox attack rate and its spatial relationship with sociodemographic and socioeconomic factors. Results From June to November 2023, a total of 1610 locally confirmed mpox cases were reported in 30 provinces in mainland China, resulting in an attack rate of 11.40 per 10 million people. Global spatial autocorrelation analysis showed that in July (Moran I=0.0938; P=.08), August (Moran I=0.1276; P=.08), and September (Moran I=0.0934; P=.07), the attack rates of mpox exhibited a clustered pattern and positive spatial autocorrelation. The Getis-Ord Gi* statistics identified hot spots of mpox attack rates in Beijing, Tianjin, Shanghai, Jiangsu, and Hainan. Beijing and Tianjin were consistent hot spots from June to October. No cold spots with low mpox attack rates were detected by the Getis-Ord Gi* statistics. Local Moran I statistics identified a high-high (HH) clustering of mpox attack rates in Guangdong, Beijing, and Tianjin. Guangdong province consistently exhibited HH clustering from June to November, while Beijing and Tianjin were identified as HH clusters from July to September. Low-low clusters were mainly located in Inner Mongolia, Xinjiang, Xizang, Qinghai, and Gansu. Ordinary least squares regression models showed that the cumulative mpox attack rates were significantly and positively associated with the proportion of the urban population (t0.05/2,1=2.4041 P=.02), per capita gross domestic product (t0.05/2,1=2.6955; P=.01), per capita disposable income (t0.05/2,1=2.8303; P=.008), per capita consumption expenditure (PCCE; t0.05/2,1=2.7452; P=.01), and PCCE for health care (t0.05/2,1=2.5924; P=.01). The geographically weighted regression models indicated a positive association and spatial heterogeneity between cumulative mpox attack rates and the proportion of the urban population, per capita gross domestic product, per capita disposable income, and PCCE, with high R2 values in north and northeast China. Conclusions Hot spots and HH clustering of mpox attack rates identified by local spatial autocorrelation analysis should be considered key areas for precision prevention and control of mpox. Specifically, Guangdong, Beijing, and Tianjin provinces should be prioritized for mpox prevention and control. These findings provide geographically precise and visualized evidence to assist in identifying key areas for targeted prevention and control.
Spatiotemporal Epidemiological Trends of Mpox in Mainland China: Spatiotemporal Ecological Comparison Study
Background The World Health Organization declared mpox an international public health emergency. Since January 1, 2022, China has been ranked among the top 10 countries most affected by the mpox outbreak globally. However, there is a lack of spatial epidemiological studies on mpox, which are crucial for accurately mapping the spatial distribution and clustering of the disease. Objective This study aims to provide geographically accurate visual evidence to determine priority areas for mpox prevention and control. Methods Locally confirmed mpox cases were collected between June and November 2023 from 31 provinces of mainland China excluding Taiwan, Macao, and Hong Kong. Spatiotemporal epidemiological analyses, including spatial autocorrelation and regression analyses, were conducted to identify the spatiotemporal characteristics and clustering patterns of mpox attack rate and its spatial relationship with sociodemographic and socioeconomic factors. Results From June to November 2023, a total of 1610 locally confirmed mpox cases were reported in 30 provinces in mainland China, resulting in an attack rate of 11.40 per 10 million people. Global spatial autocorrelation analysis showed that in July (Moran I=0.0938; P=.08), August (Moran I=0.1276; P=.08), and September (Moran I=0.0934; P=.07), the attack rates of mpox exhibited a clustered pattern and positive spatial autocorrelation. The Getis-Ord Gi* statistics identified hot spots of mpox attack rates in Beijing, Tianjin, Shanghai, Jiangsu, and Hainan. Beijing and Tianjin were consistent hot spots from June to October. No cold spots with low mpox attack rates were detected by the Getis-Ord Gi* statistics. Local Moran I statistics identified a high-high (HH) clustering of mpox attack rates in Guangdong, Beijing, and Tianjin. Guangdong province consistently exhibited HH clustering from June to November, while Beijing and Tianjin were identified as HH clusters from July to September. Low-low clusters were mainly located in Inner Mongolia, Xinjiang, Xizang, Qinghai, and Gansu. Ordinary least squares regression models showed that the cumulative mpox attack rates were significantly and positively associated with the proportion of the urban population (t0.05/2,1=2.4041 P=.02), per capita gross domestic product (t0.05/2,1=2.6955; P=.01), per capita disposable income (t0.05/2,1=2.8303; P=.008), per capita consumption expenditure (PCCE; t0.05/2,1=2.7452; P=.01), and PCCE for health care (t0.05/2,1=2.5924; P=.01). The geographically weighted regression models indicated a positive association and spatial heterogeneity between cumulative mpox attack rates and the proportion of the urban population, per capita gross domestic product, per capita disposable income, and PCCE, with high R2 values in north and northeast China. Conclusions Hot spots and HH clustering of mpox attack rates identified by local spatial autocorrelation analysis should be considered key areas for precision prevention and control of mpox. Specifically, Guangdong, Beijing, and Tianjin provinces should be prioritized for mpox prevention and control. These findings provide geographically precise and visualized evidence to assist in identifying key areas for targeted prevention and control.
Swinepox virus: an unusual outbreak in free-range pig farms in Sicily (Italy)
Background Two outbreaks of swinepox were investigated in free-range domestic pig farms located in the northeastern side of Sicily, Italy. The disease is generally self-limiting with a low mortality rate, but morbidity can reach high rates in case of poor sanitary conditions, improper husbandry practices and ectoparasitic infestation. The presented cases are the first ever reported on the island and part of the few cases reported in domestic pigs. Case presentation Carcasses condemned at the slaughterhouse and deceased pigs from Farm A and Farm B respectively, were referred for post-mortem examination and further investigations, with a strong suspect of SwinePox virus (SWPV) infection. Twelve deceased pigs were examined in total, showing poor body condition and pustular lesions scattered all over the cutaneous surfaces. Moreover, pigs from Farm B showed ocular lesions classified from Grade I to IV (from mild conjunctivitis to severe keratoconjunctivitis with corneal oedema, opacity, and ulcers). Final diagnosis was pursued by the microscopic assessment of skin lesions in both farms, which revealed the typical SWPV-lesion appearance, such as severe and disseminated ulcerative dermatitis and suspected inclusion bodies multifocally observed in the epidermis. Moreover, negative staining Electron Microscopy (nsEM) was performed on skin lesions and ocular swabs from Farm B, revealing in two samples the presence of brick-shaped viral particles, 220 nm long and 160 nm wide, with irregularly arranged surface tubules, identified as SWPV. The gene encoding the 482-bp fragment of the virus late transcription factor–3 was detected by PCR and sequencing revealed 99.79% identity and 100% query-cover with a strain previously isolated in Germany. Field clinical assessment was then performed in Farm B, revealing high overcrowding, poor sanitary conditions and improper husbandry practices, which are relevant risk factors for SWPV transmission. Conclusions The present is the first case report of SWPV in free-range pigs raised in Sicily, an island of the Southern coast of Italy, and wants to raise awareness on a neglected disease, and cause of animal health and welfare issues.
Spatiotemporal Epidemiological Trends of Mpox in Mainland China: Spatiotemporal Ecological Comparison Study (Preprint)
BACKGROUND The World Health Organization declared mpox an international public health emergency. Since January 1, 2022, China has been ranked among the top 10 countries most affected by the mpox outbreak globally. However, there is a lack of spatial epidemiological studies on mpox, which are crucial for accurately mapping the spatial distribution and clustering of the disease. OBJECTIVE This study aims to provide geographically accurate visual evidence to determine priority areas for mpox prevention and control. METHODS Locally confirmed mpox cases were collected between June and November 2023 from 31 provinces of mainland China excluding Taiwan, Macao, and Hong Kong. Spatiotemporal epidemiological analyses, including spatial autocorrelation and regression analyses, were conducted to identify the spatiotemporal characteristics and clustering patterns of mpox attack rate and its spatial relationship with sociodemographic and socioeconomic factors. RESULTS From June to November 2023, a total of 1610 locally confirmed mpox cases were reported in 30 provinces in mainland China, resulting in an attack rate of 11.40 per 10 million people. Global spatial autocorrelation analysis showed that in July (Moran <i>I</i>=0.0938; <i>P</i>=.08), August (Moran <i>I</i>=0.1276; <i>P</i>=.08), and September (Moran <i>I</i>=0.0934; <i>P</i>=.07), the attack rates of mpox exhibited a clustered pattern and positive spatial autocorrelation. The Getis-Ord Gi<sup>*</sup> statistics identified hot spots of mpox attack rates in Beijing, Tianjin, Shanghai, Jiangsu, and Hainan. Beijing and Tianjin were consistent hot spots from June to October. No cold spots with low mpox attack rates were detected by the Getis-Ord Gi<sup>*</sup> statistics. Local Moran <i>I</i> statistics identified a high-high (HH) clustering of mpox attack rates in Guangdong, Beijing, and Tianjin. Guangdong province consistently exhibited HH clustering from June to November, while Beijing and Tianjin were identified as HH clusters from July to September. Low-low clusters were mainly located in Inner Mongolia, Xinjiang, Xizang, Qinghai, and Gansu. Ordinary least squares regression models showed that the cumulative mpox attack rates were significantly and positively associated with the proportion of the urban population (<i>t<sub>0.05/2,1</sub></i>=2.4041 <i>P</i>=.02), per capita gross domestic product (<i>t<sub>0.05/2,1</sub></i>=2.6955; <i>P</i>=.01), per capita disposable income (<i>t<sub>0.05/2,1</sub></i>=2.8303; <i>P</i>=.008), per capita consumption expenditure (PCCE; <i>t<sub>0.05/2,1</sub></i>=2.7452; <i>P</i>=.01), and PCCE for health care (<i>t<sub>0.05/2,1</sub></i>=2.5924; <i>P</i>=.01). The geographically weighted regression models indicated a positive association and spatial heterogeneity between cumulative mpox attack rates and the proportion of the urban population, per capita gross domestic product, per capita disposable income, and PCCE, with high <i>R</i><sup>2</sup> values in north and northeast China. CONCLUSIONS Hot spots and HH clustering of mpox attack rates identified by local spatial autocorrelation analysis should be considered key areas for precision prevention and control of mpox. Specifically, Guangdong, Beijing, and Tianjin provinces should be prioritized for mpox prevention and control. These findings provide geographically precise and visualized evidence to assist in identifying key areas for targeted prevention and control.
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