Background: Understanding the SARS-COV-2 reinfection rate and its potential influencing factors is essential for further improvement and development of prevention and control strategies and measures to reduce the reinfection rate of SARS-CoV-2. This study aimed to quantitatively summarize the evidence of current reinfection studies. Methods: We reviewed all English studies published up to Dec 4, 2022. Information extracted from each selected articles and quality assessment of these articles was used to evaluate the risk for bias in studies. The meta-analysis was performed to examine the rate and influencing factors of SARS-CoV-2 reinfection and protective effect of primary infection on reinfection in our study. Sources of heterogeneity were identified using a subgroup analysis defined by the minimum time interval of days to reinfection and variant strains. Results: The weighted pooled rate of reinfection for SARS-CoV-2 was 1.08% ([95% CI, 0.77%-1.52%], I2 = 100%, P < 0.001). Subgroup-analysis of the minimum time interval definition for reinfection showed that rates of reinfection are 0.71%, 0.75%, 1.46% and 1.62% in less than 90 days, 90 days, greater than 90 days, unknown groups, respectively and 0.64%,1.8%,3.08%,0.95% in Alpha, Delta, Omicron, unknown groups. The weighted pooled RR value of the protective effect of primary infection on reinfection was 0.09 ([95% CI, 0.06-0.13], I2 = 92%, P < 0.01). Conclusions: Overall, the reinfection rate of SARS-CoV-2 is relatively low and appears to be on the rise as duration from the first infection to the second infection and the novel coronavirus strain mutates.

Michael P. Ward*, Victoria J. BrookesSydney School of Veterinary Science, The University of SydneyNSW, Australia*Private Mailbag 4003, Narellan NSW 2567; [email protected]

African Swine Fever Virus (ASFV) causes a deadly disease of pigs which spread through southeast Asia in 2019. We investigated one of the first outbreaks of ASFV in Lao Peoples Democratic Republic amongst smallholder villages of Thapangtong District, Savannakhet Province. In this study, two ASFV affected villages were compared to two unaffected villages. Evidence of ASFV-like clinical signs appeared in pig herds as early as May 2019, with median epidemic days on 1 and 18 June in the two villages, respectively. Using participatory epidemiology mapping techniques, we found statistically significant spatial clustering in both outbreaks (P < 0.001). Villagers reported known risk factors for ASFV transmission − such as free-ranging management systems and wild boar access − in all four villages. The villagers reported increased pig trader activity from Vietnam before the outbreaks; however, the survey did not determine a single outbreak source. The outbreak caused substantial household financial losses with an average of 9 pigs lost to the disease, and Monte Carlo analysis estimated this to be USD 215 per household. ASFV poses a significant threat to food and financial security in smallholder communities such as Thapangtong, where 40.6% of the district’s population are affected by poverty. This study shows ASFV management in the region will require increased local government resources, knowledge of informal trader activity and wild boar monitoring alongside education and support to address intra-village risk factors such as free-ranging, incorrect waste disposal and swill feeding.

Avian influenza (AI) is a contagious disease of birds with zoonotic potential. AI virus (AIV) can infect most bird species, but clinical signs and mortality vary. Assessing the distribution and factors affecting AI incidence can direct targeted surveillance to areas at risk of disease outbreaks, or help identify disease hotspots or areas with inadequate surveillance. Using virus surveillance data from passive and active AIV wild bird surveillance, 20062020, we investigated the association between a range of landscape factors and game bird release and the presence of AIV. Furthermore, we assessed potential bias in the passive AIV surveillance data submitted by the public, via factors related to public accessibility. Lastly, we tested the AIV data for possible hot and cold spots within Denmark. The passive surveillance data was biased regarding accessibility to areas (distance to roads, cities and coast) compared to random locations within Denmark. We found significant effects of variables related to coast, wetlands and cities for the passive and active AIV surveillance data (P< 0.01), but found no significant effect of game bird release. We used these variables to predict the risk of AIV presence throughout Denmark, and found high-risk areas concentrated along the coast and fjords. For both passive and active surveillance data, low-risk clusters were mainly seen in Jutland and northern Zealand, whereas high-risk clusters were found in Jutland, Zealand, Funen and the southern Isles such as Lolland and Falster. Our results suggest that landscape affects AIV presence, as coastal areas and wetlands attract waterfowl and migrating birds and therefore might increase the potential for AIV transmission. These findings have enabled us to create risk maps of AIV incidence in wild birds and pinpoint high-risk clusters within Denmark. This will aid targeted surveillance efforts within Denmark and potentially aid in planning the location of future poultry farms.

African Swine Fever Virus (ASFV) is a highly contagious pathogen causing disease in pigs, commonly characterised by acute haemorrhagic fever. Prior to August 2018, African Swine Fever (ASF) had not been reported in Asia, but has since spread throughout China, Mongolia, Korea, Vietnam, Laos, Cambodia, Myanmar, the Philippines, Hong Kong, Indonesia, Timor-Leste and Papua New Guinea. Using data collated from reports of confirmed cases, we applied spatio-temporal analysis to describe ASFV spread throughout Asia, from 1 August 2018 (reported start date) to 31 December 2019. Analysis revealed a propagating epidemic of ASFV throughout Asia, with peaks corresponding to increased reports from China, Vietnam and Laos. Two clusters of reported outbreaks were found. During the epidemic, ASFV primarily spread from the North-East to the South-East: a larger, secondary cluster in the North-East represented earlier reports, whilst the smaller, primary cluster in the South-East was characterised by later reports. Significant differences in country-specific epidemics, morbidity, mortality and unit types were discovered, likely attributable to differences in prevention, surveillance and control measures. The initial number of outbreaks and enterprise size are likely predictors of the speed of spread and the effectiveness of ASFV stamping out procedures. Biosecurity methods, wild boar populations and the transportation of pigs and movement of infected fomites are discussed as likely risk factors for facilitating ASFV spread across Asia.

African Swine Fever Virus (ASFV) causes a deadly disease of pigs which spread through southeast Asia in 2019. We investigated one of the first outbreaks of ASFV in Lao Peoples Democratic Republic amongst smallholder villages of Thapangtong District, Savannakhet Province. In this study, two ASFV affected villages were compared to two unaffected villages. Evidence of ASFV-like clinical signs appeared in pig herds as early as May 2019, with median epidemic days on 1 and 18 June in the two villages, respectively. Using participatory epidemiology mapping techniques, we found statistically significant spatial clustering in both outbreaks (P < 0.001). Villagers reported known risk factors for ASFV transmission  such as free-ranging management systems and wild boar access  in all four villages. The villagers reported increased pig trader activity from Vietnam before the outbreaks; however, the survey did not determine a single outbreak source. The outbreak caused substantial household financial losses with an average of 9 pigs lost to the disease, and Monte Carlo analysis estimated this to be USD 215 per household. ASFV poses a significant threat to food and financial security in smallholder communities such as Thapangtong, where 40.6% of the district’s population are affected by poverty. This study shows ASFV management in the region will require increased local government resources, knowledge of informal trader activity and wild boar monitoring alongside education and support to address intra-village risk factors such as free-ranging, correct waste disposal and swill feeding.

Since 2007, African swine fever virus (ASFV) has spread to countries in Europe, Asia and Oceania, and has caused devastating impacts on pigs and the pork industry. Transmission can be direct or indirect, and epidemiologic scenarios have been described in which spread occurs between free-living and domestic pigs. The purpose of this scoping review was to identify primary research in which authors made statements to support ASFV transmission between free-living and domestic pigs and assess the circumstances in which transmission events occurred. A search was conducted in five bibliographic databases and the grey literature. Two reviewers (from a team of ten) independently screened each record and charted data (demographics of the pig populations, their husbandry [domestic pigs] and habitat [free-living pigs], the spatial and temporal distribution of ASF, the occurrence or burden of ASF in the populations, and whether ticks were present in the geographic range of the pig populations). Data synthesis included statistics and a narrative summary. From 1,349 records screened, data were charted from 46 individual studies published from 1985 to 2020. Outbreak investigations revealed that whilst poor biosecurity of domestic pig operations was often reported, direct contact resulting in transmission between free-living and domestic pigs was rarely reported. Studies in which quantitative associations were made generally found that spread within populations was more important than spread between populations, although this was not always the case, particularly when domestic pigs were free-ranging. We conclude that there is limited evidence that transmission of ASFV between free-living and domestic pigs is an important feature of ASF epidemiology, especially in the current ASF epidemic in Europe and the Russian Federation. If ASFV elimination cannot be achieved in free-living pigs, compartmentalisation of free-living and domestic pig populations via biosecurity strategies could be used to support trade of domestic pigs.

There is growing evidence that climatic factors could influence the evolution of the current COVID-19 pandemic. Here, we build on this evidence base, focusing on the southern hemisphere summer and autumn period. The relationship between climatic factors and COVID-19 cases in New South Wales, Australia was investigated during both the exponential and declining phases of the epidemic in 2020, and in different regions. Increased relative humidity was associated with decreased cases in both epidemic phases, and a consistent negative relationship was found between relative humidity and cases. Overall, a decrease in relative humidity of 1% was associated with an increase in cases of 7-8%. Overall, we found no relationship with between cases and temperature, rainfall or wind speed. Information generated in this study confirms humidity as a driver of SARS-CoV-2 transmission.

Previous research has identified a relationship between climate and occurrence of SARS-CoV and MERS-CoV cases, information that can be used to reduce the risk of infection. Using COVID-19 notification and postcode data from New South Wales, Australia during the exponential phase of the epidemic in 2020, we used time-series analysis to investigate the relationship between 749 cases of locally-acquired COVID-19 and daily rainfall, 9am and 3pm temperature, and 9am and 3pm relative humidity. Lower 9am relative humidity (but not rainfall or temperature) was associated with increased case occurrence; a reduction in relative humidity of 1% was predicted to be associated with an increase of COVID-19 cases by 6.11%. During periods of low relative humidity, the public health system should anticipate an increased number of COVID-19 cases.