Thursday, August 27, 2020

On The Origin Of The Home Of COVID-19 - 16


I have pointed out in previous posts of this series, in various ways, that meat, eggs, and offal transport microbes and viruses (On The Origin Of The Home Of COVID-19, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15).

It has been known in the realms of microbiology and virology for some time that hundreds of species of bacteria inhabit the stomach (rumen) of animals that become food on our tables at meal time, or in Big Macs and Whoppers.

Not to mention the food on our plates at restaurants.

This has caused serious concern to some international entities:
[in the rumen]"Bacteria... (> 200 species) ..." (p. 11)
...
"Both human health and disease are often linked to ruminant animals: health through the nutritive value of meat and dairy products, and disease predominantly through the direct spread of zoonotic organisms or the contamination of food and the environment with manure. Worldwide the meat industry has found itself in the midst of controversy over a number of large-scale food-borne contamination incidents. These include bovine spongiform encephalopathy (BSE), E. coli O157:H7 infection, Salmonella typhimurium DT 104 with multiple antibiotic resistance, and chemical residues, which have led to the perception that meat, is not always a 'safe' product."
...
"The animal industry not only produces meat but is also the source of manure and waste effluent which are used as fertiliser. Manure and effluent are potential sources of contamination by enteric pathogens to crops (both for animal and human consumption) and waterways (Wallace, 1999; McQuigge et al., 2000). The upsurge in organic farming with increased use of manure could be a source of increased contamination if manure is not properly stored or composted (Himathongkham et al., 1999; Guan and Holley, 2003; Duffy, 2003). It is paradoxical that incidences of food-borne disease are increasing in industrialised countries. The factors involved in this increasing incidence are complex: production and distribution systems for food have changed as well as eating and cooking habits, and there is increased movement of people globally (Altekruse and Swerdlow, 1996; Lederberg, 1997)."
...
"Current intensive animal husbandry practises promote pathogens in the animal populations through contaminated feed (often by rodents or birds), and environmental (soil and water) contamination (Johnston, 1990; McEwan and Fedorka-Cray, 2002). Potential pathways for the spread of these organisms from animals to humans are shown in Figure 2. There is also concern that intensive animal production systems may be contributing to the evolution of antibiotic resistance in human infections through the transmission of resistant gut bacteria and associated genetic elements from animals to humans (Khachatourians, 1998; McEwan and Fedorka-Cray, 2002)." (p. 20)
...
"Rumen Bacteriophage diversity: Bacteriophages are abundant (107 – 109 particles per ml) in the rumen ecosystem but the diversity of these viruses is poorly understood as well as their interactions with the other microorganisms in this ecosystem. They appear to influence other microbial population structure and density through bacterial lysis in the rumen as well as being intimately involved in the exchange of genetic information with other microbial populations (Klieve et al., 1991; Klieve and Swain, 1993; Swain et al., 1996; Klieve and Hegarty, 1999). The first comprehensive metagenomic analysis of the bovine rumen virome was reported recently in which 28,000 different viral genotypes were identified (Berg Miller et al., 2012)."
...
"The genotypes belonged to the following Families in descending order of prevalence; Siphoviridae, Myoviridae, Podoviridae, Unclassified, Herpesviridae, Phycodnaviridae, Mimiviridae, Poxviridae, Baculoviridae, Iridoviridae, Polydnaviridae, Adenoviridae, Bicaudaviridae. Prophages dominated lytic phages by 2:1." [Bacteria and archaea serve as natural hosts to these families - in other words bacteria are he natural homes of viruses]
...
"The sequence analysis indicated that the phages [viruses] were associated with the main bacterial phyla including Firmicutes, Proteobacteria and Bacteroidetes thus suggesting a role in shaping these bacterial communities. Rumen phage also influence the efficiency of digestion in the rumen through the spontaneous lysis of bacterial populations by lytic phage which will also influence protein supply to the animal from microbial protein synthesized in the rumen (Swain et al., 1996)." (pp. 27-28)
(COMMISSION ON GENETIC RESOURCES FOR FOOD AND AGRICULTURE MICRO-ORGANISMS AND RUMINANT DIGESTION: STATE OF KNOWLEDGE, TRENDS AND FUTURE PROSPECTS, emphasis added). It is disconcerting that "Unclassified" is the forth most prevalent inhabitant of the rumen of animals that become food in countries around the world.

II. Coronavirus In Food Animals

It has also been know for some time that the coronavirus is rampant in food animals:
"Bovine respiratory disease (BRD) has a major impact on the cattle industry, with economic losses occurring due to morbidity, mortality, treatment and prevention costs, loss of production, and reduced carcass value (1). Infectious agents associated with BRD include viruses [bovine herpesvirus-1 (BHV-1), bovine parainfluenza-3 (PI-3V), bovine viral diarrhea virus (BVDV) 1 and 2, bovine respiratory syncytial virus (BRSV), bovine adenoviruses (BAdV), bovine coronavirus (BCV)], and bacteria (Mannheimia haemolytica, Pasteurella multocida, Histophilus somni, and Mycoplasma spp.) (1,2). From the virus standpoint, BCV has received recent attention as BRD continues to be a problem in the industry, despite the presence and widespread use of modified live virus (MLV) and killed BHV-1, BVDV, PI-3V, and BRSV products.
...
"Clinicians and diagnosticians are often called upon to examine for agents other than the 4 viruses listed, bacteria, and Mycoplasma spp. Bovine coronavirus (BCV) has been identified in cattle pulled and treated for BRD and/or in healthy cattle in numerous studies in the United States and Canada and in European countries using viral isolations from nasal swabs and serology-detecting seroconversions indicating active infections (3,4,5−12). These cited studies have focused on virus isolations from the nasal cavity for the materials for virus isolation. Bovine coronavirus has also been identified in pneumonic lungs, often in combination with other viruses, bacteria, and/or Mycoplasma spp. (2,13,14). Experimental studies have identified BCV-infected cattle with epithelial lesions in the turbinates, trachea, and lungs as well as with interstitial pneumonia (15)."
...
"Previous studies have demonstrated that the presence or absence of various levels of BCV antibodies can be used to predict whether a calf would be treated in the feedlot (9,10). Several studies have indicated that cattle may be shedding BCV in the nasal secretions on arrival at the feedlot (d 0) or perhaps before delivery to the feedlot (6,12). It is therefore important to examine practices in the beef-breeding herd and the immune status of the calves for BCV before their entry into the auction-market system where they might be exposed to cattle that are shedding BCV. The objectives of the present study were to: 1) compare BCV antibody levels in beef calves from different herds in samples collected post-weaning and before commingling with other herds; 2) correlate serum BCV antibodies in fresh calves (ranch-reared, non-commingled) collected before delivery to commercial feedlot with treatment for BRD after arrival at the feedlot; and 3) use virus isolation from nasal swabs and from lungs and serology to determine the dynamics of BCV infection in commingled, mixed-source calves transported to a research feedlot." (The Canadian Journal of Veterinary Research, p. 191)
...
"Of the 22 calves used as sentinel calves in OSU-1, 9 out of 22 (40.9%) were BCV virus positive in both the nasal swabs and the BAL samples on the day of processing, day 0 (Table I). Calves shedding the virus on day 0 cleared the virus by day 8 as nasal swab and BAL samples were all negative at collection day 8. Convalescent serum was not collected from 2 of the calves as 1 calf died with BRD (#562) and another calf (#544) was removed from the study due to lameness. Fifteen of the remaining 20 sentinel calves (75%) seroconverted. Calves that were shedding BCV at day 0 had BCV antibody levels of 8, 4, or , 4 on day 0, whereas calves with BCV antibody titers of 32 or higher at d 0 did not shed virus during the study, although they often seroconverted. Six sentinel animals remained healthy and seroconverted to BCV."
...
"The current study also identified and confirmed that calves com- mingled from mixed sources, from auction-market sources, and from wide geographic regions across the midwestern and south-central US states probably have BCV-active infections upon delivery to the feedlot and are shedding the virus. Similar to those in other studies, the calves in this study cleared the infections by day 8 after arrival. Also similar to other studies, the virus was found in the nasal swabs. In this study, BCV was also recovered in lung samples [bronchoalveolar lavage (BAL)], which were collected along with the nasal swabs. While BCV is not unlike other viruses that are shed in the nasal swabs during active infections, the finding of the BCV in the lung-derived samples suggests that BVC probably plays a role in lung lesions such as pneumonias."
...
"Bovine coronavirus (BCV) appears to be an early type of infection among the commingled calves. Calves in 2 different groups in this study identified BCV infections (nasal swab and BAL virus isolations) from sick calves in the first 4 d after arrival, but not from calves from 5 to 14 d after arrival. Another aspect of this study was that BCV was recovered from some healthy calves as well. In addition, active infections for BCV appear quite common as noted by the large number of seroconversions in both sick and healthy animals. It is common to find seroconversions to several bovine viruses among cattle under feedlot conditions as noted for BVDV, PI-3V, and BRSV (20,21)." (p. 197)
(Bovine coronavirus (BCV) infections in transported commingledbeef cattle and sole-source ranch calves, The Canadian Journal of Veterinary Research, 2011; 75:191–199, emphasis added).

III. All In The Family

The coronavirus "family" is noted in the genomic data of SARS-CoV-2 (SARS coronavirus 2) as has been shown in previous posts in this series.

In other words, the genetic data indicates that the SARS-CoV-2 coronavirus can be found in humans, poulty, swine, and cattle.

It is not at all unusual to find a caronavirus in humans, poulty, swine, and cattle:
"Coronaviruses (CoVs) cause respiratory and gastrointestinal disease in humans, poultry, swine, and cattle."
(Emerging Infectious Diseases • www.cdc.gov/eid • Vol. 26, No. 2, February 2020, p. 255). That is keeping it in the family:
"Coronavirus is the common name for Coronaviridae and Orthocoronavirinae, also called Coronavirinae. Coronaviruses cause diseases in mammals and birds. In humans, the viruses cause respiratory infections, including the common cold, which are typically mild, though rarer forms such as SARS (including the one causing COVID-19) and MERS can be lethal. Symptoms vary in other species: in chickens, they cause an upper respiratory disease, while in cows and pigs coronaviruses cause diarrhea. There are no vaccines or antiviral drugs to prevent or treat human coronavirus infections. They are enveloped viruses with a positive-sense single-stranded RNA genome and a nucleocapsid of helical symmetry. The genome size of coronaviruses ranges from approximately 26 to 32 kilobases, among the largest for an RNA virus (second only to a 41-kb nidovirus recently discovered in planaria)."
(Wikipedia, emphasis added). The coronavirus lineage evinces  a lot of changes because of the way they are "made" (the destruction of their natural place inside bacteria when antibiotics and other toxins destroy their "home").

IV. Closing Comments

Look through the following appendices (to previous posts in this series) and you will see lists of the lineage of SARS-CoV-2 in animals and humans going back to Coronaviridae (Appendix MT276327 A, Appendix MN997409 C, Appendix AN-1-99).

Remember to be careful when a friend or colleague tells you, as you are driving down a road after a hurricane, "that sign we just passed that said 'bridge out ahead' is not proof that the bridge ahead is really out".

There are different kinds of proof (I like to tell some of my lawyer friends that "proof" is something the jury provides ... all we can provide is "evidence").

The next post in this series is here, the previous post in this series is here.

Tuesday, August 25, 2020

On The Origin Of The Home Of COVID-19 - 15

The mass-slaughter-of-animals-for-food industry
Some six years ago I indicated that mistreatment of the flora and fauna of the Earth could lead to events that much of the media and many researchers would blame on microbes and viruses, but which in reality were caused by civilization's mistreatment of the Earth's environment (The Real Dangers With Microbes & Viruses, What Did The Mass Extinctions Do To Viruses and Microbes).

In this current series I have pointed out the undisputed reality that a relevant portion of the mistreatment of flora and fauna is done by "the mass-slaughter-of-animals-for-food industry" (On The Origin Of The Home Of COVID-19, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14).

For example:
"To meet this demand [commercialization / population growth], there are several approaches being in force like antibiotic / antimicrobial / hormonal growth promotors. But these methods also lead to major public health concerns ranging from residues to antimicrobial resistance in human population ... It is a well-known fact that microbiota plays a pivotal role in the gastrointestinal health in ruminant and nonruminant animals."
...
"For generations, farmers have used antibiotics to improve production of their chicken, pig, and cattle operations. With use of certain antibiotics on the chopping block because of concerns about the rise of resistant organisms, some are turning from anti to pro—probiotics, that is.

Probiotics, live microorganisms that are a staple of the human wellness industry, have the potential to fulfill many of the roles that antibiotics play down on the farm. Research suggests probiotics can help chickens, pigs, and cows quickly put on weight, efficiently digest feed, and withstand the infectious organisms that tend to lurk wherever animals are kept in close quarters ... But farmers have several ways to raise healthy livestock without relying on antibiotics."
(On The Origin Of The Home Of COVID-19). In other words, it is no secret that "the mass-slaughter-of-animals-for-food industry" is a source of "major public health concerns".

Nor is it a secret that "the mass-slaughter-of-animals-for-food industry" exports its products in a multi-billion dollar annual business:
"Tyson Foods, Inc. is an American multinational corporation based in Springdale, Arkansas, that operates in the food industry. The company is the world's second largest processor and marketer of chicken, beef, and pork after JBS S.A. and annually exports the largest percentage of beef out of the United States. Together with its subsidiaries, it operates major food brands, including Jimmy Dean, Hillshire Farm, Ball Park, Wright Brand, Aidells, and State Fair. Tyson Foods ranked No. 80 in the 2018 Fortune 500 list of the largest United States corporations by total revenue."
...
"'The U.S. food system is a complex network of farmers and the industries that link to them. Those links include makers of farm equipment and chemicals as well as firms that provide services to agribusinesses, such as providers of transportation and financial services. The system also includes the food marketing industries that link farms to consumers, and which include food and fiber processors, wholesalers, retailers, and food service establishments'.

The term food industries covers a series of industrial activities directed at the processing, conversion, preparation, preservation and packaging of foodstuffs. The food industry today has become highly diversified, with manufacturing ranging from small, traditional, family-run activities that are highly labor intensive, to large, capital-intensive and highly mechanized industrial processes. Many food industries depend almost entirely on local agriculture or fishing."
...
"Rarely found on menus in the U.S., variety meat – also called offal or fancy meat – takes many forms: kidneys, livers, stomachs, tendons, aortas, cheek meat, oxtails and more. And because it's highly sought after in key export markets of Egypt, Japan, Peru and Mexico, variety meat [offal] is gold to the U.S. beef industry.

According to the U.S. Meat Export Federation, total U.S. beef exports in 2012 set a new record at $5.51 billion. Beef offal represented $703.1 million, or about 12% of that. It also accounted for 28.4% of the total volume of beef exports.

And, virtually 100% of the U.S. livestock herd is represented in variety meat exports [offal] – some part of every animal is sold to international customers.

'Demand for both large and small intestines would tank without the international market,' says Jerry Wiggs, export salesman for Greater Omaha Packing Company Inc. (OPC). 'We are selling large intestines to South Korea or Koreans who recently moved to the U.S.'

Wiggs says OPC just recently resumed selling small intestines to Mexico, where they had been banned since BSE was found in the U.S. in late 2003."
...
"Edible offal products, which are made from an animal’s intestines, internal organs, and other parts, rarely end up on American plates. Does that mean it simply goes to waste?

Thanks in large part to international trade, the answer is no. Culinary traditions in countries around the world call for the use offal in a wide variety of dishes ... In many places, certain offal products are even considered a delicacy. By looking beyond America’s borders, meat processors have been able to uncover lucrative markets and reach new consumers hungry for American food products.

Consider the case of Mexico, a country that consistently ranks as one of the leading importers of U.S. offal products, also known as “variety meats”. One of the most popular products is tripe, an offal made from a cow’s stomach."
(On The Origin Of The Home Of COVID-19 - 10). The post also points out that 78% of the food fed to mink on mink farms is offal, so when the talking point that "viruses or microbes can't be spread in food" comes your way don't fall for it.

The US offal export business (which the mink farming business relies on for mink food) has caused major damage to countries it has been exporting to, because that commodity is an element of diet:
"The Netherlands is one of 24 countries where mink farming is still legal. In a historic move, the Dutch parliament has voted to permanently close the mink fur farms shut down by COVID-19.
...
The spread of COVID-19 among mink across multiple farms since April resulted in at least two workers catching the virus from the animals and triggered calls for the government to rapidly shut down the industry. “Waiting until 2024 for the mink ban to take effect would have been unjustifiable and irresponsible,” says Sandra Schoenmakers, director of Dutch anti-fur organizations Bont voor Dieren. The latest available figures show that nearly 600,000 mink across 13 farms had been killed by gassing with carbon monoxide on the orders of the Dutch government, but many more are likely to be killed in the coming weeks.

Factory farms and slaughterhouses across the world have become coronavirus hotbeds due to cramped and unsafe working conditions, endangering the lives of workers who have been given inadequate protection by the companies that employ them. While transmission between workers on the Dutch mink farms has not reached the levels seen on agricultural farms, it presents the first case in which humans passed the virus to the farmed animals who then transmitted it back to humans.
...
The intensive breeding of animals on fur farms is an incredibly cruel practice that not only causes immense suffering to animals, but can also serve as a reservoir for coronaviruses
".
(On The Origin Of The Home Of COVID-19 - 12). Yes, diet is important, and yes microbes can be passed to those who consume food with microbes in it:
"Editorial Summary

Minor role for host genetics in shaping the microbiota

The composition of the human gut microbiome is determined by many factors. Eran Segal and colleagues performed an extensive statistical analysis of the largest metagenomics-sequenced human cohort so far to determine the contribution of host genotype to microbiome composition. Host genetics has only a minor influence on microbiome variability, which is more strongly associated with environmental factors such as diet. The authors propose a 'microbiome-association index' that describes the association of the microbiome with host phenotype. Combining this measurement with host genetic and environmental data improves the accuracy of predictions about several human metabolic traits, such as glucose and obesity traits."
...
"A wealth of evidence suggests that this incredibly diverse microbial community is regulated by host genetic factors, and more importantly, environmental and dietary factors (4–6)"."
...
"Human gut microbiome composition is shaped by multiple factors but the relative contribution of host genetics remains elusive. Here we examine genotype and microbiome data from 1,046 healthy individuals with several distinct ancestral origins who share a relatively common environment, and demonstrate that the gut microbiome is not significantly associated with genetic ancestry, and that host genetics have a minor role in determining microbiome composition. We show that, by contrast, there are significant similarities in the compositions of the microbiomes of genetically unrelated individuals who share a household, and that over 20% of the inter-person microbiome variability is associated with factors related to diet, drugs and anthropometric measurements. We further demonstrate that microbiome data significantly improve the prediction accuracy for many human traits, such as glucose and obesity measures, compared to models that use only host genetic and environmental data. These results suggest that microbiome alterations aimed at improving clinical outcomes may be carried out across diverse genetic backgrounds."
(ibid). Exported food and food distributed in country by "the mass-slaughter-of-animals-for-food industry" has been a danger to public health for who knows how long.

The two tables below are an updated/corrected list of countries that "the mass-slaughter-of-animals-for-food industry" may or may not export its products to:

About Columns in the HTML table below:

'Country' is a list of 92 nations that receive USA exports
'Abbr' is the abbreviation of the country's name used in .gov reports
'Gets exports?' indicates if the USDA indicates US exports go to that country
'Virus data?' indicates if SARS-CoV-2 genomes are in GenBank
'Phase 1' means SARS-CoV-2 records I found in GenBank on or before 23/Aug/2020
'Phase 2' means records I found in GenBank between 23/Aug/2020 and 2/22/2021
'Total' means: total reports I found in GenBank for that country



USDA Export Report on meat, offal, and eggs
exported to the following countries (along with the count
of SARS-CoV-2 genomes recorded in GenBank from there)
as follows:

Country Abbr Gets
exports?
Virus
data?
Phase 1 Phase 2 Total
Afghanistan AFG yes no 0 0 0
Aland ALA yes no 0 0 0
Albania ALB yes no 0 0 0
Algeria DZA yes no 0 0 0
American Samoa ASM yes no 0 0 0
Andorra AND yes yes 2,648 0 2,648
Angola AGO yes no 0 0 0
Anguilla AIA yes no 0 0 0
Antarctica ATA yes no 0 0 0
Antigua and Barbuda ATG yes no 0 0 0
Argentina ARG yes yes 0 20 20
Armenia ARM yes no 0 0 0
Aruba ABW yes no 0 0 0
Australia AUS yes yes 1,115 9,354 10,469
Austria AUT yes yes 5 0 5
Azerbaijan AZE yes no 0 0 0
Bahamas BHS yes no 0 0 0
Bahrain BHR yes yes 8 115 123
Bangladesh BGD yes yes 122 208 330
Barbados BRB yes no 0 0 0
Belarus BLR yes no 0 0 0
Belgium BEL yes yes 22 1 23
Belize BLZ yes yes 0 4 4
Benin BEN yes yes 0 12 12
Bermuda BMU yes no 0 0 0
Bhutan BTN yes no 0 0 0
Bolivia BOL yes no 0 0 0
Saba BQ yes no 0 0 0
Bosnia
and
Herzegovina
BIH yes no 0 0 0
Botswana BWA yes no 0 0 0
Bouvet BVT yes no 0 0 0
Brazil BRA yes yes 129 11 140
British
Indian Ocean
Territory
IOT yes no 0 0 0
Brunei BN yes no 0 0 0
Bulgaria BGR yes yes 3 0 3
Burkina Faso BFA yes yes 3 0 3
Burundi BDI yes no 0 0 0
Verde CPV yes no 0 0 0
Cambodia KHM yes yes 0 1 1
Cameroon CMR yes yes 5 0 5
Canada CAN yes yes 22 3 25
Cayman CYM yes no 0 0 0
Central African
Republic
CAF yes no 0 0 0
Chad TCD yes no 0 0 0
Chile CHL yes yes 9 244 253
China CHN yes yes 4,187 12 4,199
Christmas CXR yes no 0 0 0
Cocos (Keeling) CCK yes no 0 0 0
Colombia COL yes yes 24 0 24
Comoros COM yes no 0 0 0
Congo COD yes no 0 0 0
Republic of
the Congo
178 yes yes 1 3 4
Cook COK yes no 0 0 0
Costa Rica CRI yes no 0 0 0
Ivory Coast CIV yes no 0 0 0
Croatia HRV yes no 0 0 0
Cuba CUB yes no 0 0 0
Curaçao CUW yes no 0 0 0
Cyprus CYP yes no 0 0 0
Czech CZE yes yes 14 0 14
Denmark DNK yes yes 8 0 8
Djibouti DJI yes no 0 0 0
Dominica DMA yes no 0 0 0
Dominican DOM yes yes 0 1 1
Ecuador ECU yes yes 1 4 5
Egypt EGY yes yes 64 428 492
El Salvador SLV yes no 0 0 0
Guinea GNQ yes yes 1 0 1
Eritrea ERI yes no 0 0 0
Estonia EST yes no 0 0 0
Eswatini SWZ yes no 0 0 0
Ethiopia ETH yes yes 10 0 10
Falkland FLK yes no 0 0 0
Faroe FRO yes no 0 0 0
Fiji FJI yes no 0 0 0
Finland FIN yes yes 2 0 2
France FRA yes yes 273 4 277
French Guiana GUF yes no 0 0 0
French Polynesia PYF yes no 0 0 0
French Southern and
Antarctic Lands
ATF yes no 0 0 0
Gabon GAB yes no 0 0 0
Gambia GMB yes no 0 0 0
Georgia GEO yes yes 8 2 10
Germany DEU yes yes 36 14 50
Ghana GHA yes yes 16 26 42
Gibraltar GIB yes no 0 0 0
Greece GRC yes yes 101 0 101
Greenland GRL yes no 0 0 0
Grenada GRD yes no 0 0 0
Guadeloupe GLP yes no 0 0 0
Guam GUM yes yes 3 0 3
Guatemala GTM yes yes 0 10 10
Guernsey GGY yes no 0 0 0
Guinea GIN yes yes 1 0 1
Guinea-Bissau GNB yes no 0 0 0
Guyana GUY yes no 0 0 0
Haiti HTI yes yes 8 0 8
Heard Island and McDonald
Islands
HMD yes no 0 0 0
Holy See VAT yes no 0 0 0
Honduras HND yes no 0 0 0
Hong Kong HKG yes yes 131 80 211
Hungary HUN yes yes 4 0 4
Iceland ISL yes no 0 0 0
India IND yes yes 279 258 537
Indonesia IDN yes no 0 0 0
Iran IRN yes yes 16 6 22
Iraq IRQ yes yes 0 29 29
Ireland IRL yes yes 1 0 1
Isle of Man IMN yes no 0 0 0
Israel ISR yes yes 11 8 19
Italy ITA yes yes 70 61 131
Jamaica JAM yes no 0 0 0
Japan JPN yes yes 282 1 283
Jersey JEY yes no 0 0 0
Jordan JOR yes yes 16 23 39
Kazakhstan KAZ yes yes 4 0 4
Kenya KEN yes yes 28 0 28
Kiribati KIR yes no 0 0 0
North Korea PRK yes no 0 0 0
South Korea KOR yes yes 562 13 575
Kuwait KWT yes no 0 0 0
Kyrgyzstan KGZ yes no 0 0 0
Laos LAO yes yes 1 0 1
Latvia LVA yes no 0 0 0
Lebanon LBN yes yes 0 4 4
Lesotho LSO yes no 0 0 0
Liberia LBR yes no 0 0 0
Libya LBY yes no 0 0 0
Liechtenstein LIE yes no 0 0 0
Lithuania LTU yes no 0 0 0
Luxembourg LUX yes no 0 0 0
Macao MAC yes no 0 0 0
Macedonia MKD yes no 0 0 0
Madagascar MDG yes no 0 0 0
Malawi MWI yes no 0 0 0
Malaysia MYS yes yes 26 2 28
Maldives MDV yes no 0 0 0
Mali MLI yes yes 0 2 2
Malta MLT yes yes 0 4 4
Marshall Islands MHL yes no 0 0 0
Martinique MTQ yes no 0 0 0
Mauritania MRT yes no 0 0 0
Mauritius MUS yes no 0 0 0
Mayotte MYT yes no 0 0 0
Mexico MEX yes yes 63 32 95
Micronesia FSM yes no 0 0 0
Moldova MDA yes no 0 0 0
Monaco MCO yes no 0 0 0
Mongolia MNG yes no 0 0 0
Montenegro MNE yes no 0 0 0
Montserrat MSR yes no 0 0 0
Morocco MAR yes yes 13 1 14
Mozambique MOZ yes no 0 0 0
Myanmar MMR yes yes 0 9 9
Namibia NAM yes no 0 0 0
Nauru NRU yes no 0 0 0
Nepal NPL yes yes 1 0 1
Netherlands NLD yes yes 103 1,529 1,632
New Caledonia NCL yes no 0 0 0
New Zealand NZL yes yes 1 0 1
Nicaragua NIC yes no 0 0 0
Niger NER yes yes 16 0 16
Nigeria NGA yes yes 15 1 16
Niue NIU yes no 0 0 0
Norfolk Island NFK yes no 0 0 0
Northern Mariana
Islands
MNP yes no 0 0 0
Norway NOR yes no 0 0 0
Oman OMN yes yes 12 0 12
Pakistan PAK yes yes 3 37 40
Palau PLW yes no 0 0 0
Palestine PS yes no 0 0 0
Panama PAN yes no 0 0 0
Papua New Guinea PNG yes no 0 0 0
Paraguay PRY yes no 0 0 0
Peru PER yes yes 3 93 96
Philippines PHL yes yes 16 24 40
Pitcairn TPC yes no 0 0 0
Poland POL yes yes 28 112 140
Portugal PRT yes no 0 0 0
Puerto Rico PRI yes yes 13 1 14
Qatar QAT yes yes 7 0 7
Réunion REU yes no 0 0 0
Romania ROU yes yes 3 0 3
Russia RUS yes yes 2 20 22
Rwanda RWA yes no 0 0 0
Saint Barthélemy BLM yes no 0 0 0
Tristan da Cunha SH yes yes 4 0 4
Saint Kitts and Nevis KNA yes no 0 0 0
Saint Lucia LCA yes no 0 0 0
Saint Martin MAF yes no 0 0 0
Saint Pierre and
Miquelon
SPM yes no 0 0 0
Saint Vincent and
the Grenadines
VCT yes no 0 0 0
Samoa WSM yes no 0 0 0
San Marino SMR yes no 0 0 0
São Tomé and
Príncipe
STP yes no 0 0 0
Saudi Arabia SAU yes yes 501 28 529
Senegal SEN yes no 0 0 0
Serbia SRB yes yes 5 137 142
Seychelles SYC yes no 0 0 0
Sierra Leone SLE yes yes 0 10 10
Singapore SGP yes yes 27 0 27
Sint Maarten SXM yes no 0 0 0
Slovakia SVK yes no 0 0 0
Slovenia SVN yes yes 3 0 3
Solomon Islands SLB yes no 0 0 0
Somalia SOM yes no 0 0 0
South Africa ZAF yes yes 4 0 4
South Georgia and the South
Sandwich Islands
SGS yes no 0 0 0
South Sudan SSD yes no 0 0 0
Spain ESP yes yes 31 20 51
Sri Lanka LKA yes yes 4 0 4
Sudan SDN yes yes 1 0 1
Suriname SUR yes no 0 0 0
Jan Mayen SJM yes no 0 0 0
Sweden SWE yes yes 48 0 48
Switzerland CHE yes no 0 0 0
Syria SYR yes no 0 0 0
Taiwan TWN yes yes 151 6 157
Tajikistan TJK yes no 0 0 0
Tanzania TZ yes yes 1 0 1
Thailand THA yes yes 132 0 132
East Timor TLS yes no 0 0 0
Togo TGO yes no 0 0 0
Tokelau TKL yes no 0 0 0
Tonga TON yes no 0 0 0
Trinidad and Tobago TTO yes no 0 0 0
Tunisia TUN yes yes 2 48 50
Turkey TUR yes yes 85 28 113
Turkmenistan TKM yes no 0 0 0
Turks and Caicos
Islands
TCA yes no 0 0 0
Tuvalu TUV yes no 0 0 0
Uganda UGA yes yes 3 0 3
Ukraine UKR yes yes 2 0 2
United Arab Emirates ARE yes yes 191 0 191
United Kingdom UK yes yes 27 0 27
United States Minor
Outlying Islands
UMI yes no 0 0 0
United States Minor
Outlying Islands
UMI yes no 1,270 19,034 20,304
Uruguay URY yes yes 3 7 10
Uzbekistan UZB yes no 0 0 0
Vanuatu VUT yes no 0 0 0
Venezuela VEN yes yes 0 6 6
Vietnam VNM yes yes 10 0 10
British Virgin Islands VGB yes no 0 0 0
United States Virgin
Islands
VIR yes no 0 0 0
Wallis and Futuna WLF yes no 0 0 0
Western Sahara ESH yes no 0 0 0
Yemen YEM yes no 0 0 0
Zambia ZMB yes yes 0 1 1
ZimbabweZWEyesno000

About Columns in the HTML table below:

'Country' is a list of 92 nations that receive USA exports
'Abbr' is the abbreviation of the country's name used in .gov reports
'Gets exports?' indicates if the USDA indicates US exports go to that country
'Virus data?' indicates if SARS-CoV-2 genomes are in GenBank
'Phase 1' means SARS-CoV-2 records I found in GenBank on or before 23/Aug/2020
'Phase 2' means records I found in GenBank between 23/Aug/2020 and 2/22/2021
'Total' means: total reports I found in GenBank for that country



USDA Export Report on meat, offal, and eggs NOT
exported to the following countries (along with the count
of SARS-CoV-2 genomes recorded in GenBank from there)
as follows:

Country Abbr Gets
exports?
Virus
data?
Phase 1 Phase 2 Total
Afghanistan AFG no no 0 0 0
Aland ALA no no 0 0 0
Albania ALB no no 0 0 0
Algeria DZA no no 0 0 0
American Samoa ASM no no 0 0 0
Andorra AND no yes 2,648 0 2,648
Angola AGO no no 0 0 0
Anguilla AIA no no 0 0 0
Antarctica ATA no no 0 0 0
Antigua and Barbuda ATG no no 0 0 0
Argentina ARG no yes 0 20 20
Armenia ARM no no 0 0 0
Aruba ABW no no 0 0 0
Australia AUS no yes 1,115 9,354 10,469
Austria AUT no yes 5 0 5
Azerbaijan AZE no no 0 0 0
Bahamas BHS no no 0 0 0
Bahrain BHR no yes 8 115 123
Bangladesh BGD no yes 122 208 330
Barbados BRB no no 0 0 0
Belarus BLR no no 0 0 0
Belgium BEL no yes 22 1 23
Belize BLZ no yes 0 4 4
Benin BEN no yes 0 12 12
Bermuda BMU no no 0 0 0
Bhutan BTN no no 0 0 0
Bolivia BOL no no 0 0 0
Saba BQ no no 0 0 0
Bosnia and Herzegovina BIH no no 0 0 0
Botswana BWA no no 0 0 0
Bouvet BVT no no 0 0 0
Brazil BRA no yes 129 11 140
British Indian Ocean
Territory
IOT no no 0 0 0
Brunei BN no no 0 0 0
Bulgaria BGR no yes 3 0 3
Burkina Faso BFA no yes 3 0 3
Burundi BDI no no 0 0 0
Verde CPV no no 0 0 0
Cambodia KHM no yes 0 1 1
Cameroon CMR no yes 5 0 5
Canada CAN no yes 22 3 25
Cayman CYM no no 0 0 0
Central African
Republic
CAF no no 0 0 0
Chad TCD no no 0 0 0
Chile CHL no yes 9 244 253
China CHN no yes 4,187 12 4,199
Christmas CXR no no 0 0 0
Cocos (Keeling) CCK no no 0 0 0
Colombia COL no yes 24 0 24
Comoros COM no no 0 0 0
Congo COD no no 0 0 0
Republic of the Congo 178 no yes 1 3 4
Cook COK no no 0 0 0
Costa Rica CRI no no 0 0 0
Ivory Coast CIV no no 0 0 0
Croatia HRV no no 0 0 0
Cuba CUB no no 0 0 0
Curaçao CUW no no 0 0 0
Cyprus CYP no no 0 0 0
Czech CZE no yes 14 0 14
Denmark DNK no yes 8 0 8
Djibouti DJI no no 0 0 0
Dominica DMA no no 0 0 0
Dominican DOM no yes 0 1 1
Ecuador ECU no yes 1 4 5
Egypt EGY no yes 64 428 492
El Salvador SLV no no 0 0 0
Guinea GNQ no yes 1 0 1
Eritrea ERI no no 0 0 0
Estonia EST no no 0 0 0
Eswatini SWZ no no 0 0 0
Ethiopia ETH no yes 10 0 10
Falkland FLK no no 0 0 0
Faroe FRO no no 0 0 0
Fiji FJI no no 0 0 0
Finland FIN no yes 2 0 2
France FRA no yes 273 4 277
French Guiana GUF no no 0 0 0
French Polynesia PYF no no 0 0 0
French Southern and
Antarctic Lands
ATF no no 0 0 0
Gabon GAB no no 0 0 0
Gambia GMB no no 0 0 0
Georgia GEO no yes 8 2 10
Germany DEU no yes 36 14 50
Ghana GHA no yes 16 26 42
Gibraltar GIB no no 0 0 0
Greece GRC no yes 101 0 101
Greenland GRL no no 0 0 0
Grenada GRD no no 0 0 0
Guadeloupe GLP no no 0 0 0
Guam GUM no yes 3 0 3
Guatemala GTM no yes 0 10 10
Guernsey GGY no no 0 0 0
Guinea GIN no yes 1 0 1
Guinea-Bissau GNB no no 0 0 0
Guyana GUY no no 0 0 0
Haiti HTI no yes 8 0 8
Heard Island and McDonald
Islands
HMD no no 0 0 0
Holy See VAT no no 0 0 0
Honduras HND no no 0 0 0
Hong Kong HKG no yes 131 80 211
Hungary HUN no yes 4 0 4
Iceland ISL no no 0 0 0
India IND no yes 279 258 537
Indonesia IDN no no 0 0 0
Iran IRN no yes 16 6 22
Iraq IRQ no yes 0 29 29
Ireland IRL no yes 1 0 1
Isle of Man IMN no no 0 0 0
Israel ISR no yes 11 8 19
Italy ITA no yes 70 61 131
Jamaica JAM no no 0 0 0
Japan JPN no yes 282 1 283
Jersey JEY no no 0 0 0
Jordan JOR no yes 16 23 39
Kazakhstan KAZ no yes 4 0 4
Kenya KEN no yes 28 0 28
Kiribati KIR no no 0 0 0
North Korea PRK no no 0 0 0
South Korea KOR no yes 562 13 575
Kuwait KWT no no 0 0 0
Kyrgyzstan KGZ no no 0 0 0
Laos LAO no yes 1 0 1
Latvia LVA no no 0 0 0
Lebanon LBN no yes 0 4 4
Lesotho LSO no no 0 0 0
Liberia LBR no no 0 0 0
Libya LBY no no 0 0 0
Liechtenstein LIE no no 0 0 0
Lithuania LTU no no 0 0 0
Luxembourg LUX no no 0 0 0
Macao MAC no no 0 0 0
Macedonia MKD no no 0 0 0
Madagascar MDG no no 0 0 0
Malawi MWI no no 0 0 0
Malaysia MYS no yes 26 2 28
Maldives MDV no no 0 0 0
Mali MLI no yes 0 2 2
Malta MLT no yes 0 4 4
Marshall Islands MHL no no 0 0 0
Martinique MTQ no no 0 0 0
Mauritania MRT no no 0 0 0
Mauritius MUS no no 0 0 0
Mayotte MYT no no 0 0 0
Mexico MEX no yes 63 32 95
Micronesia FSM no no 0 0 0
Moldova MDA no no 0 0 0
Monaco MCO no no 0 0 0
Mongolia MNG no no 0 0 0
Montenegro MNE no no 0 0 0
Montserrat MSR no no 0 0 0
Morocco MAR no yes 13 1 14
Mozambique MOZ no no 0 0 0
Myanmar MMR no yes 0 9 9
Namibia NAM no no 0 0 0
Nauru NRU no no 0 0 0
Nepal NPL no yes 1 0 1
Netherlands NLD no yes 103 1,529 1,632
New Caledonia NCL no no 0 0 0
New Zealand NZL no yes 1 0 1
Nicaragua NIC no no 0 0 0
Niger NER no yes 16 0 16
Nigeria NGA no yes 15 1 16
Niue NIU no no 0 0 0
Norfolk Island NFK no no 0 0 0
Northern Mariana
Islands
MNP no no 0 0 0
Norway NOR no no 0 0 0
Oman OMN no yes 12 0 12
Pakistan PAK no yes 3 37 40
Palau PLW no no 0 0 0
Palestine PS no no 0 0 0
Panama PAN no no 0 0 0
Papua New Guinea PNG no no 0 0 0
Paraguay PRY no no 0 0 0
Peru PER no yes 3 93 96
Philippines PHL no yes 16 24 40
Pitcairn TPC no no 0 0 0
Poland POL no yes 28 112 140
Portugal PRT no no 0 0 0
Puerto Rico PRI no yes 13 1 14
Qatar QAT no yes 7 0 7
Réunion REU no no 0 0 0
Romania ROU no yes 3 0 3
Russia RUS no yes 2 20 22
Rwanda RWA no no 0 0 0
Saint Barthélemy BLM no no 0 0 0
Tristan da Cunha SH no yes 4 0 4
Saint Kitts and Nevis KNA no no 0 0 0
Saint Lucia LCA no no 0 0 0
Saint Martin MAF no no 0 0 0
Saint Pierre and
Miquelon
SPM no no 0 0 0
Saint Vincent and
the Grenadines
VCT no no 0 0 0
Samoa WSM no no 0 0 0
San Marino SMR no no 0 0 0
São Tomé and
Príncipe
STP no no 0 0 0
Saudi Arabia SAU no yes 501 28 529
Senegal SEN no no 0 0 0
Serbia SRB no yes 5 137 142
Seychelles SYC no no 0 0 0
Sierra Leone SLE no yes 0 10 10
Singapore SGP no yes 27 0 27
Sint Maarten SXM no no 0 0 0
Slovakia SVK no no 0 0 0
Slovenia SVN no yes 3 0 3
Solomon Islands SLB no no 0 0 0
Somalia SOM no no 0 0 0
South Africa ZAF no yes 4 0 4
South Georgia and the South
Sandwich Islands
SGS no no 0 0 0
South Sudan SSD no no 0 0 0
Spain ESP no yes 31 20 51
Sri Lanka LKA no yes 4 0 4
Sudan SDN no yes 1 0 1
Suriname SUR no no 0 0 0
Jan Mayen SJM no no 0 0 0
Sweden SWE no yes 48 0 48
Switzerland CHE no no 0 0 0
Syria SYR no no 0 0 0
Taiwan TWN no yes 151 6 157
Tajikistan TJK no no 0 0 0
Tanzania TZ no yes 1 0 1
Thailand THA no yes 132 0 132
East Timor TLS no no 0 0 0
Togo TGO no no 0 0 0
Tokelau TKL no no 0 0 0
Tonga TON no no 0 0 0
Trinidad and Tobago TTO no no 0 0 0
Tunisia TUN no yes 2 48 50
Turkey TUR no yes 85 28 113
Turkmenistan TKM no no 0 0 0
Turks and Caicos
Islands
TCA no no 0 0 0
Tuvalu TUV no no 0 0 0
Uganda UGA no yes 3 0 3
Ukraine UKR no yes 2 0 2
United Arab Emirates ARE no yes 191 0 191
United Kingdom UK no yes 27 0 27
United States Minor
Outlying Islands
UMI no no 0 0 0
United States USA no yes 1,270 19,034 20,304
Uruguay URY no yes 3 7 10
Uzbekistan UZB no no 0 0 0
Vanuatu VUT no no 0 0 0
Venezuela VEN no yes 0 6 6
Vietnam VNM no yes 10 0 10
British Virgin Islands VGB no no 0 0 0
United States Virgin
Islands
VIR no no 0 0 0
Wallis and Futuna WLF no no 0 0 0
Western Sahara ESH no no 0 0 0
Yemen YEM no no 0 0 0
Zambia ZMB no yes 0 1 1
ZimbabweZWEnono000

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