Lecture on Food Security and Protection.

by Alonzo A. Gabriel, Ph.D., RMPAM

1. 6/8/17&
1&
Food$Security$&$Protection$Quality(|(Safety(|(Defense(
Alonzo$A.$Gabriel,$Ph.D.,$RMPAM$(UP$Diliman)$
[email protected]$
Download handout from our FB page!
IG:&@LFMH_UPD&
Food Security: An Evolving Concern
Food Adequacy Hunger
Food Security: An Evolving Concern
Food Adequacy Hunger

2. 6/8/17&
2&
Food Security: An Evolving Concern
Food Adequacy
Food Adequacy +
Food Safety
Hunger
Hunger
Infectious Diseases
Food Security: An Evolving Concern
Food Adequacy
Food Adequacy +
Food Safety
Food Adequacy +
Food Safety +
Food Defense
Hunger
Hunger
Infectious Diseases
Hunger
Infectious Diseases
‘Man-Made’ Diseases
Food Security: An Evolving Concern
Food Adequacy
Food Adequacy +
Food Safety
Food Adequacy +
Food Safety +
Food Defense
Food Adequacy +
Food Safety +
Food Defense +
Food Quality
Hunger
Hunger
Infectious Diseases
Hunger
Infectious Diseases
‘Man-Made’ Diseases
Hunger
Infectious Diseases
‘Man-Made’ Diseases
Lifestyle Diseases
Physical(Spoilage(
(Bio)Chemical(Spoilage(
Biological(Spoilage(
(
Why$process
1
$food?$
1
Cooking$is$a$form$of$food$processing$

3. 6/8/17&
3&
Spoiled?$
Can$you$still$eat$it?$
Spoiled?$
Can$you$still$eat$it?$
Spoiled?$
Can$you$still$eat$it?$
Spoiled?$
Can$you$still$eat$it?$

4. 6/8/17&
4&
(((The(loss$of$desirable$
quality$of(food(
products(
Spoilage$
(((How(does(vinegar(
spoil?(
(
Spoilage:$Loss$of$desirable$food$quality$
(((Can(we(eat(‘spoiled’(
food(products?(
(
((((Yes!(But(will(
depend(on(the(
nature(of(spoilage(
Spoilage$
Anthracnose due to
Colletotrichum gloeosporiodes
Mummyberry due to
Monilinia vaccinii
Will$you$get$sick$if$you$eat$these?$

5. 6/8/17&
5&
Moldy bread due to
Rhizopus stolonifer
Bacterial soft rot in carrots due to
Erwinia carotovora
Will$you$get$sick$if$you$eat$these?$
http://www.sfgate.com/science/article/Masses-of-food-wasted-use-by-dates-mislead-4825974.php
Diarrhea(and(malnutrition(combine(to(form(a(vicious(
cycle(leading(to(declining(health(status$
Motarjemi&et&al.,&1993&
Impact$of$Foodborne$Illnesses$
Foodborne$illnesses$and$child$growth$

6. 6/8/17&
6&
Infectious$diseases$in$the$early$1900s$
(United$States)$
Cohen,'2000'
Infectious$diseases$in$the$late$1900s$
(United$States)$
Cohen,'2000'
In$the$developing$world…$
! A(different(picture…(
! 1998:'Mortality'due'to'infectious'diseases:'
13'M'(ca.$25%'of'deaths'worldwide)'
! Pneumonia((3.5'M)(
! Diarrhea((2.2'M)(
! TB((1.5'M)(
! AIDS,(malaria,(measles((ca.$4.4'M)(
Cohen,'2000'
Dates$to$remember$

7. 6/8/17&
7&
What$is$wrong$with$this$picture?$
What$is$wrong$with$this$picture?$
Culture$and$
traditional$beliefs$
can$be$major$
hindrances$in$
attaining$food$
safety.$
The$Food$‘Superhighways’$
Series
www.thelancet.com Vol 380 December 1, 2012 1949
burden shortly after introduction, especially on a local
scale, as the fraction of the population that is immune to
infection rises.
14
This pattern both contrasts with, and has
similarities to, the emergence of endemic diseases.
Emergence of endemic pathogens
Emergence of endemic VBPs is frequently associated
with changes in land use
33
or socioeconomic conditions,
34

and these transitions control the dynamics of disease
emergence. For pathogens aff ected by land-use change,
the rise in case numbers is often gradual (fi gure 1),
paralleling changes in the pathogen’s abiotic and biotic
environment. By contrast, the increased incidence of
endemic disease driven by changes in socioeconomic
conditions can be abrupt if the shift is rapid, such as that
caused by political upheavals, military confl icts, or
natural disasters (fi gure 1).
Changes in land use aff ect VBPs by altering the inter-
actions and abundance of wildlife and domestic hosts,
vectors, and people, with some diseases better understood
than are others.
33
In the Amazon and east Africa,
deforestation increases standing water and sunlight and
enhances the breeding success of some mosquito
species, which can increase risk of malaria. Further
increases in urbanisation frequently eliminate anoph-
eline mosquito habitat and have reduced malaria
elsewhere.
35
In northeastern North America, reforestation
during the 20th cen tury is thought to have allowed
recolonisation by deer and the consequent expansion of
the range of ticks (Ixodes scapularis), under pinning the
emergence of Lyme disease in the mid-20th century.
36

Deer (Odocoileus virginianus in the USA and Capreolus
capreolus in Europe) have a key role in feeding adult
Ixodes ticks, although they are actually incompetent hosts
for the Lyme disease bacterial spirochaetes. Additionally,
in the past three decades, fragmentation of forests in
eastern regions of Canada and the USA and changes in
predator communities
37
have altered the host community
for ticks and the Lyme bacterium Borrelia burgdorferi, and
might have increased relative abun dance of small
mammals (white-footed mice [Peromyscus leucopus],
eastern chipmunks [Tamias striatus], and shrews [Sorex
spp and Blarina brevicauda]) that are the principal
transmission hosts for Lyme disease spirochaetes. These
changes in the host community can result in increased
spirochaete infection prevalence in nymphal ticks.
38

A key remaining question is how fragmentation and
hunting-induced changes in the host community aff ect
the abundance of infected nymphal ticks, which is the
key metric for disease risk.
Changes in land use might also be responsible for
recent emergent foci of Crimean-Congo haemorrhagic
fever virus within its large range through parts of Africa,
Asia, southeastern Europe, and the Middle East. By
contrast with typical sporadic outbreaks of only a few
cases, an exceptional epidemic occurred in Turkey, starting
with about 20 cases in 2002, and rising to nearly 1400 cases
by 2008 (fi gure 1). Most infections occurred in agricultural
and animal husbandry workers via tick bites and direct
contamination from infected animals. Changes in land
cover associated with political unrest and reduced agri-
cultural activities might have allowed colonisation by
wildlife and subsequent tick population growth, as is
thought to have precipitated the fi rst recorded epidemic
of Crimean-Congo haemorrhagic fever in Crimea in
1944–45.
39
The case fatality rate (5%) in Turkey has been
Figure 2: The global aviation network
Lines show direct links between airports, and the colour indicates passenger capacity in people per day (thousands [red]; hundreds [yellow]; tens [blue]). Routes
linking regions at similar latitudes (in the northern or southern hemisphere) represent pathways that pathogens can move along to reach novel regions. Notably, air
traffi c to most places in Africa, regions of South America, and parts of central Asia is low. If travel increases in these regions, additional introductions of vector-borne
pathogens are probable. Adapted from Hufnagal and colleagues.
30

8. 6/8/17&
8&
+
Multi-state/national outbreaks
Finland
Ohio
Michigan
Arizona
Molecular epidemiology revealed that the causative agent was Salmonella Stanley
Australia
+
Kennedy (2010)
Our$Concerns$
Food(Security(
Food(Adequacy(Food(Safety(Food(Defense(
Empty$
Calories$

9. 6/8/17&
9&
(((The(assurance(that(there(will(be(
enough(calories(for(the(population’s(
health(and(wellPbeing.(
Food$Adequacy$Food$Poisoning$
Food$Poisoning$
Challenges and Opportunities
Occurrences of foodborne illness outbreaks are mostly from micro,
small, and medium scale food manufacturers/ food service
establishments that have limited access to Food Safety Education.

10. 6/8/17&
10&
Challenges and Opportunities Challenges and Opportunities
Principle 4

Food business operators, at
every stage of the food chain,
have the primary role and
responsibility for ensuring the
safety of their food products.

Special consideration should be
given to small and medium-size
enterprises (SMEs) by the
regulatory authorities to enable
them to upgrade their food safety
assurance systems…

(((The(assurance(that(illnesses(will(not(
result(from(consuming(foods(due(to(
naturally(occurring(hazards;(makes(
sure(that(food(will(not(cause(illnesses(
when(consumed(in(their(intended(use.(
Food$Safety$ Food$Poisoning$

11. 6/8/17&
11&
Amino Acid
Amino Group Nitrogen
"Nitrogen = "Quality
Milk$quality$and$protein$content$
Melamine
Non-Amino Group Nitrogen
FALSE Quality Indicator!!!
Milk$quality$and$protein$content$
Intentional$Contamination$Food$Fraud:$Fake$Meat$

12. 6/8/17&
12&
Food$Fraud:$Fake$Beef$Food$Fraud:$Fake$Eggs$
Food$Fraud:$Fake$Rice$
JAMA,&1987&
Food$as$Weapon$
Original Contributions
A Large Community Outbreak
of Salmonellosis Caused by Intentional
Contamination of Restaurant Salad Bars
Thomas J. To¨ro¨k, MD; Robert V. Tauxe, MD, MPH; Robert P. Wise, MD, MPH; John R. Livengood, MD;
Robert Sokolow; Steven Mauvais; Kristin A. Birkness; Michael R. Skeels, PhD, MPH;
John M. Horan, MD, MPH; Laurence R. Foster, MD, MPH†
Context.—This large outbreak of foodborne disease highlights the challenge of
investigating outbreaks caused by intentional contamination and demonstrates the
vulnerability of self-service foods to intentional contamination.
Objective.—To investigate a large community outbreak of Salmonella Typhi-
murium infections.
Design.—Epidemiologic investigation of patients with Salmonella gastroenteri-
tis and possible exposures in The Dalles, Oregon. Cohort and case-control inves-
tigations were conducted among groups of restaurant patrons and employees to
identify exposures associated with illness.
Setting.—A community in Oregon. Outbreak period was September and Octo-
ber 1984.
Patients.—A total of 751 persons with Salmonella gastroenteritis associated with
eating or working at area restaurants. Most patients were identified through pas-
sive surveillance; active surveillance was conducted for selected groups. A case
was defined either by clinical criteria or by a stool culture yielding S Typhimurium.
Results.—The outbreak occurred in 2 waves, September 9 through 18 and
September 19 through October 10. Most cases were associated with 10 restau-
rants, and epidemiologic studies of customers at 4 restaurants and of employees
at all 10 restaurants implicated eating from salad bars as the major risk factor for
infection. Eight (80%) of 10 affected restaurants compared with only 3 (11%) of the
28 other restaurants in The Dalles operated salad bars (relative risk, 7.5; 95% con-
fidence interval, 2.4-22.7; P!.001). The implicated food items on the salad bars
differed from one restaurant to another. The investigation did not identify any water
supply, food item, supplier, or distributor common to all affected restaurants, nor
were employees exposed to any single common source. In some instances,
infected employees may have contributed to the spread of illness by inadvertently
contaminating foods. However, no evidence was found linking ill employees to ini-
tiation of the outbreak. Errors in food rotation and inadequate refrigeration on ice-
chilled salad bars may have facilitated growth of the S Typhimurium but could not
have caused the outbreak. A subsequent criminal investigation revealed that
members of a religious commune had deliberately contaminated the salad bars. An
S Typhimurium strain found in a laboratory at the commune was indistinguishable
from the outbreak strain.
Conclusions.—This outbreak of salmonellosis was caused by intentional con-
tamination of restaurant salad bars by members of a religious commune.
JAMA. 1997;278:389-395
OUTBREAKS of foodborne infection
are caused by foods that are intrinsically
contaminated or that become contami-
nated during harvest, processing, or
preparation. It is generally assumed that
such contamination events occur inad-
vertently; intentional contamination
with a biologic agent is rarely suspected
or reported.
1,2
On September 17, 1984, the Wasco-
Sherman Public Health Department in
Oregon began to receive reports of per-
sons ill with gastroenteritis who had eaten
at either of 2 restaurants in The Dalles,
Ore, several days before symptom onset.
Local and state public health officials con-
firmed an outbreak of Salmonella Typhi-
murium associated with the 2 restaurants
and then noted an abrupt increase in re-
ports of gastroenteritis the following
week among persons who had eaten or
worked at other restaurants in The
Dalles. Because many patients reported
eating food from salad bars, the local
health department closed all salad bars in
the town on September 25, 1984, and the
Oregon Health Division requested assis-
tance from the Centers for Disease Con-
trol (CDC) for further evaluation and con-
trol of the outbreak.
The epidemiologic investigation identi-
fied the vehicles of transmission as foods
on multiple self-service salad bars and
probable times when contamination oc-
curred. Common mechanisms by which
salad bars could have become contami-
nated were excluded. A subsequent crimi-
nal investigation found that members of a
nearby religious commune had intention-
ally contaminated the salad bars on mul-
tiple occasions.
From the National Center for Infectious Diseases
and Epidemiology Program Office, Centers for
Disease Control and Prevention, Atlanta, Ga
(Drs To¨ro¨k,Tauxe,Wise,Livengood,andHoranand
Ms Birkness); and the Oregon Health Division,
Portland (Messrs Sokolow and Mauvais and
Drs Skeels and Foster). Dr Wise is now with the US
Food and Drug Administration.
†Deceased.
Presented in part in the Congressional Record, Feb-
ruary 28, 1985; 99th Congress, 1st Session: H901-
H905, and at the Epidemic Intelligence Service 34th
annual conference, Atlanta, Ga, April 23, 1985.
Trade names are used for identification only and
does not imply endorsement by the US Department
of Health and Human Services or the US Public
Health Service.
Reprints: Thomas J. To¨ro¨ k, MD, Centers for Disease
Control and Prevention, Mailstop G-17, 1600 Clifton Rd
NE, Atlanta, GA 30333.
BACKGROUND
The Dalles, population 10 500 (1980
census), is the county seat of Wasco
County, population 21 000, a region of or-
chards and wheat ranches. Located near
the Columbia River on Interstate 84,
The Dalles is a frequent stop for travel-
JAMA, August 6, 1997—Vol 278, No. 5 Intentional Restaurant Salad Bar Contamination—To¨ro¨k et al 389
©1997 American Medical Association. All rights reserved.

13. 6/8/17&
13&
So$what’s$the$difference?!$
Original Contributions
A Large Community Outbreak
of Salmonellosis Caused by Intentional
Contamination of Restaurant Salad Bars
Thomas J. To¨ro¨k, MD; Robert V. Tauxe, MD, MPH; Robert P. Wise, MD, MPH; John R. Livengood, MD;
Robert Sokolow; Steven Mauvais; Kristin A. Birkness; Michael R. Skeels, PhD, MPH;
John M. Horan, MD, MPH; Laurence R. Foster, MD, MPH†
Context.—This large outbreak of foodborne disease highlights the challenge of
investigating outbreaks caused by intentional contamination and demonstrates the
vulnerability of self-service foods to intentional contamination.
Objective.—To investigate a large community outbreak of Salmonella Typhi-
murium infections.
Design.—Epidemiologic investigation of patients with Salmonella gastroenteri-
tis and possible exposures in The Dalles, Oregon. Cohort and case-control inves-
tigations were conducted among groups of restaurant patrons and employees to
identify exposures associated with illness.
Setting.—A community in Oregon. Outbreak period was September and Octo-
ber 1984.
Patients.—A total of 751 persons with Salmonella gastroenteritis associated with
eating or working at area restaurants. Most patients were identified through pas-
sive surveillance; active surveillance was conducted for selected groups. A case
was defined either by clinical criteria or by a stool culture yielding S Typhimurium.
Results.—The outbreak occurred in 2 waves, September 9 through 18 and
September 19 through October 10. Most cases were associated with 10 restau-
rants, and epidemiologic studies of customers at 4 restaurants and of employees
at all 10 restaurants implicated eating from salad bars as the major risk factor for
infection. Eight (80%) of 10 affected restaurants compared with only 3 (11%) of the
28 other restaurants in The Dalles operated salad bars (relative risk, 7.5; 95% con-
fidence interval, 2.4-22.7; P!.001). The implicated food items on the salad bars
differed from one restaurant to another. The investigation did not identify any water
supply, food item, supplier, or distributor common to all affected restaurants, nor
were employees exposed to any single common source. In some instances,
infected employees may have contributed to the spread of illness by inadvertently
contaminating foods. However, no evidence was found linking ill employees to ini-
tiation of the outbreak. Errors in food rotation and inadequate refrigeration on ice-
chilled salad bars may have facilitated growth of the S Typhimurium but could not
have caused the outbreak. A subsequent criminal investigation revealed that
members of a religious commune had deliberately contaminated the salad bars. An
S Typhimurium strain found in a laboratory at the commune was indistinguishable
from the outbreak strain.
Conclusions.—This outbreak of salmonellosis was caused by intentional con-
tamination of restaurant salad bars by members of a religious commune.
JAMA. 1997;278:389-395
OUTBREAKS of foodborne infection
are caused by foods that are intrinsically
contaminated or that become contami-
nated during harvest, processing, or
preparation. It is generally assumed that
such contamination events occur inad-
vertently; intentional contamination
with a biologic agent is rarely suspected
or reported.
1,2
On September 17, 1984, the Wasco-
Sherman Public Health Department in
Oregon began to receive reports of per-
sons ill with gastroenteritis who had eaten
at either of 2 restaurants in The Dalles,
Ore, several days before symptom onset.
Local and state public health officials con-
firmed an outbreak of Salmonella Typhi-
murium associated with the 2 restaurants
and then noted an abrupt increase in re-
ports of gastroenteritis the following
week among persons who had eaten or
worked at other restaurants in The
Dalles. Because many patients reported
eating food from salad bars, the local
health department closed all salad bars in
the town on September 25, 1984, and the
Oregon Health Division requested assis-
tance from the Centers for Disease Con-
trol (CDC) for further evaluation and con-
trol of the outbreak.
The epidemiologic investigation identi-
fied the vehicles of transmission as foods
on multiple self-service salad bars and
probable times when contamination oc-
curred. Common mechanisms by which
salad bars could have become contami-
nated were excluded. A subsequent crimi-
nal investigation found that members of a
nearby religious commune had intention-
ally contaminated the salad bars on mul-
tiple occasions.
From the National Center for Infectious Diseases
and Epidemiology Program Office, Centers for
Disease Control and Prevention, Atlanta, Ga
(Drs To¨ro¨k,Tauxe,Wise,Livengood,andHoranand
Ms Birkness); and the Oregon Health Division,
Portland (Messrs Sokolow and Mauvais and
Drs Skeels and Foster). Dr Wise is now with the US
Food and Drug Administration.
†Deceased.
Presented in part in the Congressional Record, Feb-
ruary 28, 1985; 99th Congress, 1st Session: H901-
H905, and at the Epidemic Intelligence Service 34th
annual conference, Atlanta, Ga, April 23, 1985.
Trade names are used for identification only and
does not imply endorsement by the US Department
of Health and Human Services or the US Public
Health Service.
Reprints: Thomas J. To¨ro¨ k, MD, Centers for Disease
Control and Prevention, Mailstop G-17, 1600 Clifton Rd
NE, Atlanta, GA 30333.
BACKGROUND
The Dalles, population 10 500 (1980
census), is the county seat of Wasco
County, population 21 000, a region of or-
chards and wheat ranches. Located near
the Columbia River on Interstate 84,
The Dalles is a frequent stop for travel-
JAMA, August 6, 1997—Vol 278, No. 5 Intentional Restaurant Salad Bar Contamination—To¨ro¨k et al 389
©1997 American Medical Association. All rights reserved.
(((The(assurance(that(illnesses(will(not(
result(from(consuming(foods(due(to(
hazards(that(are(intentionally(
introduced(to(them.(
Food$Defense$
# Found: US
Agricultural
documents
translated in
Arabic, intended
for agricultural
terrorism of
crops, livestock,
food processing
operations.
1442(sick(from(1(truck!(
Food$Safety$or$Food$Defense?$

14. 6/8/17&
14&
Scope(of(Food(Defense(
Food(Defense(
Economically(
Motivated(
Bioterrorism(
Emerging$Concepts$
Food(Security(
Food(Adequacy(Food(Safety(Food(Defense(
! (Consumers(
! 'Zero$risk$
! (Industry(
! 'Acceptable$risk$
What$is$safe$food?$
! 'Zero(risk'is'not(possible…'
! 'But'risks'can(be(minimized!(
The$(sad)$truth$is…$

15. 6/8/17&
15&
Production Processing Distribution Consumption
So$who’s$at$fault?!$
Physical$Hazards$
Chemical$Hazards$
Biological$Hazards$
Radiological$Hazards$
Physical$Hazards$(Filth)$

16. 6/8/17&
16&
Physical$Hazards$(Filth)$
! 'Hair'
! 'Metal'
! 'Glass'
! 'Soil'
! 'Wood'
! 'Insect'Parts(
Chemical$Hazards$
! 'Pesticides'
! 'Toxic'metals'
! 'Detergents'
! 'Additives/'''
''''''Preservatives(
Want$to$know$what’s$in$your$
cheeseburger?$

17. 6/8/17&
17&
Biological$Hazards$
! 'Bacteria'
! 'Fungi''! Yeasts'and'Molds'
! 'Viruses'
! 'Parasites'
1. Taenia$solium((pork)$
2. Taenia$saginata$(beef)$
3. Enterobius$vermicularis$
4. Ascaris$lumbricoides$
5. Paragonimus$westermani$
IFT (2002)
Foodborne$parasites$

18. 6/8/17&
18&
Tapeworm$Diet?$Tapeworm$Diet?$
Sundathelphusa$philippina$Bacteria$
! Bacteria'are'responsible'for'
foodborne'illnesses'that'
require'hospitalization.'

19. 6/8/17&
19&
Kennedy (2010)
Some$more$(sad)$truths…$
! All'raw'foods'contain'certain'
amounts'of'microorganisms…'
! Most'food'processing'
techniques'reduce,'not'
eliminate'microorganisms…'
Some$more$(sad)$truths…$
! Microorganisms'are'easily'reY
introduced'to'cooked'or'
processed'foods'when'
improperly'handled.'
Bacteria$are$ubiquitous$
! Intestinal'tracts'of'
healthy'humans'
and'animals'
! Human'and'
animal'wastes'
! Human'skin'
surfaces'and'nasal'
passages'
! Soil'and'
vegetation'

20. 6/8/17&
20&
Handwashing$ Hand$hygiene$
Safe_uard$says…$
! It'kills'99.9%(of(
germs!(
Safe_uard$says…$
10,000(
100,000(

21. 6/8/17&
21&
You$are$only$10%$human!$
For'every'human'
cell'on/in'you,'there(
are(10(‘foreigners’(
‘hitch(hiking’(
(
You'have'10
13
((
human(cells(
100,000,000,000,000(
Then$washing$with$soap$alone…$
Then$washing$with$soap$alone…$You$are$your$microbes$

22. 6/8/17&
22&
You$and$your$microbes$
Each'human'has'a'
microbial$signature(
(microbiome)$
that'in[luences'his/
her'health/disease.'
You$and$your$microbes$
The'diversity'of'one’s'
microbiome'is'affected'
by:'
'
$ genetic$makeup$
$ microbes$encountered$
through$the$life$cycle$
$ diet$
You$and$your$microbes$
Food'made'up'of'
complex'molecules'
will'need'more'
diverse'microbiota.'
People$with$diabetes$
have$less$microbial$
diversity$in$their$guts.$
You$and$your$microbes$
Obesity(and'other'
diseases'are'now'
being'linked'with'
our'microbiome.''
People$with$high$energyA
harvesting$efBiciency$
microbiota$are$more$
likely$to$become$obese.$

23. 6/8/17&
23&
You$are$your$microbes$
http://upload.wikimedia.org/wikipedia/en/0/0a/Skin_Microbiome20169-300.jpg
Pregnancy
Fecal microbiota Fecal microbiota
Transfer of microbiota from mother to child
National Academy of Science, 2014
Copyright © National Academy of Sciences. All rights reserved.
Microbial Ecology in States of Health and Disease: Workshop Summary
WORKSHOP OVERVIEW 39
changes in the composition of the fecal microbiota of the STAT mice. Coincident
with these changes, key genes involved in fat metabolism were up-regulated in
the livers of STAT mice, Blaser reported. This research suggests that in STAT
mice, the liver receives increased quantities of short-chain fatty acids produced
by microbes in the intestine and converts them into fat; these fat calories are then
transported to adipose tissue for storage. Current studies suggest that early-life
antibiotic exposures in the mouse model are sufficient for lifelong physiological
changes (Cho et al., 2012).
These results led Blaser’s group to investigate whether a series of short,
therapeutic-dose pulses of antibiotics administered in early life—an experience
shared by many U.S. children—could produce sufficient change in the mouse
gut microbiome to alter body composition; as demonstrated in the mouse model,
preliminary results suggests lifelong effects. Blaser observed that studies in other
fields may help to illuminate these results. Similar patterns have been observed
in forest ecosystems, he noted, which tend to recover from infrequent distur-
bances unless a second disturbance follows before stability is restored (Paine et
al., 1998).
FIGURE WO-18 Factors modifying mother-to-child microbial transmission. Through
live birth, mammals have important opportunities for mother-to-child microbial transmis-
sion through direct surface contact. However, many modern practices can reduce organism
and gene flow; several examples are illustrated.
SOURCE: Cho and Blaser (2012).
Development of the human microbiota
National Academy of Science, 2014
Copyright © National Academy of Sciences. All rights reserved.
Microbial Ecology in States of Health and Disease: Workshop Summary
28 MICROBIAL ECOLOGY IN STATES OF HEALTH AND DISEASE
FIGURE WO-13 The development of the microbiota from the first inoculum as an infant
through continued change, modified by diet, genetics, and environment, throughout life.
SOURCE: Domínguez-Bello et al. (2011).
initially resembles its mother’s vaginal microbiome, with Lactobacilli dominat-
ing in the infant gut. Babies born by Caesarean section are initially colonized by
species associated with skin and dominated by taxa including Staphylococcus
and Propionibacterium spp.—a composition that persists for several months
following birth (Domínguez-Bello et al., 2010). Initial assembly of the infant
gut microbiome may have implications for the early and long-term health of the
host. The infant microbiome provides resistance to pathogen invasion, furnishes
developmental cues, and influences immunological functions. Recent research
has demonstrated that colonization during the neonatal period strongly influences
mucosal immune development (reviewed in Costello et al., 2012; Lozupone et
al., 2012).
Just how differences in microbial community composition in the early stages
of life may influence disease susceptibility at later stages of life is not well under-
stood. Investigators have recently described intriguing associations between the
composition of the microbiota of children born by Caesarean section and their
subsequent development of asthma (Couzin-Frankel, 2010). These results suggest
that early colonization events might be deterministic—imparting substantial and
lasting effects on the immune system—irrespective of the composition of the ma-
ture microbiome. The ways in which factors such as the environment (including
diet) and life events (illness, puberty, and pregnancy) influence the community
composition of the human gut from birth to old age is an area of active investiga-
tion (Domínguez-Bello et al., 2011; Lozupone et al., 2012; Maynard et al., 2012).
Following initial colonization events, the gut microbiota of human adults
undergoes consecutive changes in composition and function, increasing in diver-
sity and stability until a relatively constant adult gut community is established
(Lozupone et al., 2012). The microbiota of “healthy” adults exists in dynamic

24. 6/8/17&
24&
Harming$your$good$microbes$is$
harming$yourself!$
! After'a'dose'of'antibiotics'
! Upset'stomach'
! Yeast'infection'
Harming$your$good$microbes$is$
harming$yourself!$
Tummy$Buddies$
Tummy$Baddy$
Harming$your$good$microbes$is$
harming$yourself!$
Harming$your$good$microbes$is$
harming$yourself!$

25. 6/8/17&
25&
Harming$your$good$microbes$is$
harming$yourself!$
Harming$your$good$microbes$is$
harming$yourself!$
Prebiotic$Transfer$Prebiotic$Transfer$
‘Processing’(
Donor$and$recipient$should$
have$‘compatible$blora’$

26. 6/8/17&
26&
Poop$banking$
Factors$leading$to$foodborne$
illnesses$
Horizontal$gene$transfer$

27. 6/8/17&
27&
Horizontal$gene$transfer$Who$are$at$risk?$
The$complexity$of$food$safety$
Foodborne
Illness
Consumer
Food &
Environment
Microbe
Consumer
Food &
Environment
Microbe
Foodborne
Illness
Consumer
Food
Microbe
Foodborne
Illness
Know$your$enemies…$
Staphylococcus$Escherichia$coli$

28. 6/8/17&
28&
Know$your$enemies…$
Vibrio$cholerae$Listeria$monocytogenes$
SPORULATION
IFT (2002)
Know$your$enemies…$
Bacillus$cereus$Clostridium$botulinum$
Know$your$enemies…$
Salmonella$enterica$Pyrodinium$bahamense$

29. 6/8/17&
29&
Foodborne$Illnesses$(US,$2011)(
CDC,&2011&
February 2011 www.cdc.gov/foodborneburden
Pathogens causing the most illnesses, hospitalizations, and deaths each year
Eight known pathogens account for the vast majority of illnesses, hospitalizations, and deaths. Tables 2–4 list the top !ve
pathogens causing illness, hospitalization, and death.
Pathogen
Estimated annual number of
illnesses
90% Credible Interval %
Norovirus 5,461,731 3,227,078–8,309,480 58
Salmonella, nontyphoidal 1,027,561 644,786–1,679,667 11
Clostridium perfringens 965,958 192,316–2,483,309 10
Campylobacter spp. 845,024 337,031–1,611,083 9
Staphylococcus aureus 241,148 72,341–529,417 3
Subtotal 91
Pathogen
Estimated annual number of
hospitalizations
90% Credible Interval %
Salmonella, nontyphoidal 19,336 8,545–37,490 35
Norovirus 14,663 8,097–23,323 26
Campylobacter spp. 8,463 4,300–15,227 15
Toxoplasma gondii 4,428 3,060–7,146 8
E. coli (STEC) O157 2,138 549–4,614 4
Subtotal 88
Pathogen
Estimated annual number of
deaths
90% Credible Interval %
Salmonella, nontyphoidal 378 0–1,011 28
Toxoplasma gondii 327 200–482 24
Listeria monocytogenes 255 0–733 19
Norovirus 149 84–237 11
Campylobacter spp. 76 0–332 6
Subtotal 88
Table 2. Top !ve pathogens causing domestically acquired foodborne illnesses
Table 3. Top !ve pathogens causing domestically acquired foodborne illnesses resulting in hospitalization
Table 4. Top !ve pathogens causing domestically acquired foodborne illnesses resulting in death
Foodborne$Illnesses$(US,$2011)(
CDC,&2011&
February 2011 www.cdc.gov/foodborneburden
Pathogens causing the most illnesses, hospitalizations, and deaths each year
Eight known pathogens account for the vast majority of illnesses, hospitalizations, and deaths. Tables 2–4 list the top !ve
pathogens causing illness, hospitalization, and death.
Pathogen
Estimated annual number of
illnesses
90% Credible Interval %
Norovirus 5,461,731 3,227,078–8,309,480 58
Salmonella, nontyphoidal 1,027,561 644,786–1,679,667 11
Clostridium perfringens 965,958 192,316–2,483,309 10
Campylobacter spp. 845,024 337,031–1,611,083 9
Staphylococcus aureus 241,148 72,341–529,417 3
Subtotal 91
Pathogen
Estimated annual number of
hospitalizations
90% Credible Interval %
Salmonella, nontyphoidal 19,336 8,545–37,490 35
Norovirus 14,663 8,097–23,323 26
Campylobacter spp. 8,463 4,300–15,227 15
Toxoplasma gondii 4,428 3,060–7,146 8
E. coli (STEC) O157 2,138 549–4,614 4
Subtotal 88
Pathogen
Estimated annual number of
deaths
90% Credible Interval %
Salmonella, nontyphoidal 378 0–1,011 28
Toxoplasma gondii 327 200–482 24
Listeria monocytogenes 255 0–733 19
Norovirus 149 84–237 11
Campylobacter spp. 76 0–332 6
Subtotal 88
Table 2. Top !ve pathogens causing domestically acquired foodborne illnesses
Table 3. Top !ve pathogens causing domestically acquired foodborne illnesses resulting in hospitalization
Table 4. Top !ve pathogens causing domestically acquired foodborne illnesses resulting in death
Foodborne$Illnesses$(US,$2011)(
CDC,&2011&
February 2011 www.cdc.gov/foodborneburden
Pathogens causing the most illnesses, hospitalizations, and deaths each year
Eight known pathogens account for the vast majority of illnesses, hospitalizations, and deaths. Tables 2–4 list the top !ve
pathogens causing illness, hospitalization, and death.
Pathogen
Estimated annual number of
illnesses
90% Credible Interval %
Norovirus 5,461,731 3,227,078–8,309,480 58
Salmonella, nontyphoidal 1,027,561 644,786–1,679,667 11
Clostridium perfringens 965,958 192,316–2,483,309 10
Campylobacter spp. 845,024 337,031–1,611,083 9
Staphylococcus aureus 241,148 72,341–529,417 3
Subtotal 91
Pathogen
Estimated annual number of
hospitalizations
90% Credible Interval %
Salmonella, nontyphoidal 19,336 8,545–37,490 35
Norovirus 14,663 8,097–23,323 26
Campylobacter spp. 8,463 4,300–15,227 15
Toxoplasma gondii 4,428 3,060–7,146 8
E. coli (STEC) O157 2,138 549–4,614 4
Subtotal 88
Pathogen
Estimated annual number of
deaths
90% Credible Interval %
Salmonella, nontyphoidal 378 0–1,011 28
Toxoplasma gondii 327 200–482 24
Listeria monocytogenes 255 0–733 19
Norovirus 149 84–237 11
Campylobacter spp. 76 0–332 6
Subtotal 88
Table 2. Top !ve pathogens causing domestically acquired foodborne illnesses
Table 3. Top !ve pathogens causing domestically acquired foodborne illnesses resulting in hospitalization
Table 4. Top !ve pathogens causing domestically acquired foodborne illnesses resulting in death
Meanwhile,$in$the$Philippines…(
Azanza,&2006&
Food$Types$Associates$with$Foodborne$Disease$Outbreaks$
(1995P2004)(
Food(Type( %(
Meat'(spaghetti,'pork'dishes,'processed'meats,'chicken,'etc.)'32(
Fish(and(Seafood(([ish'dishes,'[ish'balls,'etc.)(20(
Bakery(Products((Egg'sandwich,'Cakes,'pies,'etc.)(17(
Toxins'(Wild'mushrooms,'Puffer'[ish,'etc.')(13(
Beverages'(Fruit'juices,'Lambanog,'etc.')(((8(
Others'(Rice'congee,'spring'rolls,'etc.)'10(

30. 6/8/17&
30&
Meanwhile,$in$the$Philippines…(
Azanza,&2006&
Causative$Agents$of$Morbidities$Associated$with$FBIs$
(1995P2004)(
Food(Type( %(
Salmonella$enterica$30(
Staphylococcal(enterotoxin(23(
Vibrio$parahaemolyticus$10(
Paralytic(shell`ish(poisoning((Red(Tide)(((4(
Vibrio$cholerae$ ((4(
Histamine( ((4(
Escherichia$coli$ ((2(
Meanwhile,$in$the$Philippines…(
Azanza,&2006&
Outbreak$Locations$of$Foodborne$Illnesses$
(1995P2004)(
Percentages(
Occurrences(Morbidity(Mortality(
Home(43( 18( 96(
Workplaces(20( 39( ((4(
Schools(15( 24( ((0(
Restaurants(12( ((8(((0(
Unknown(10( 11( ((0(
Eggs$are$smart!$
Germ$spot$
Yolk$
Shell$
Thin$white$
Thick$white$
Inner$membrane$
Outer$membrane$Chalazae$
Air$cell$
Cuticle$
Avidin,$Lysozyme,$etc.$
NO$antimicrobial$agents$in$yolk!!!$
Salmonella$is$smarter$
Transovarian$infection$
of$eggs$by$Salmonella$

31. 6/8/17&
31&
What$is$wrong$with$this$picture?$Analyses$for$specibic$bacteria$
are$expensive…$
! Pathogens'are'fastidious'and'
require'expensive'techniques'
for'detection.''
Analyses$for$specibic$bacteria$
are$expensive…$
! Total(Aerobic(Plate(Counts'
(TPC)'as'indicator'of'food'
hygiene.'
! Counts'of'10
5
(cells/gram(is'
still'considered'acceptable.'
'
Counting$bacteria$in$foods$

32. 6/8/17&
32&
Microbiology$of$selected$
readygtogeat$food$
Reminders$
! All'foods'were'sampled'from'
UP'Campus'canteens,'
ambulant'vendors,'etc.'
! Analyses'replications'ranged'
from'3Y9'times.''
Reminders$
! Samplings'were'conducted'
over'a'4Yyear'period.'
! Photos'presented'are'NOT'of'
the'actual'samples.''
Stewed$osso(bucco(with$
vegetables$and$peanut$sauce$$
2.55(×(10
4(
cells/g(
Azanza,(2005(

33. 6/8/17&
33&
Fried$jerked$beef$
3.70(×(10
6(
cells/g(
Azanza,(2005(
Pork$and$vegetable$sour$
stew$
1.90(×(10
4(
cells/g(
Azanza,(2005(
Grilled$pork$slices$
3.61(×(10
5(
cells/g(
Azanza,(2005(
Chopped$grilled$spicy$pork$
jowls/masks$
1.35(×(10
4(
cells/g(
Azanza,(2005(

34. 6/8/17&
34&
Fried$sweet$nitritegcured$
pork$slices$
8.50(×(10
4(
cells/g(
Azanza,(2005(
Grilled$pork$kebabs$
6.07(×(10
5(
cells/g(
Azanza,(2005(
Fried$Chinese$meat$roll$
4.57(×(10
5(
cells/g(
Azanza,(2005(
Grilled$chicken$intestine$
kebabs$
2.58(×(10
4(
cells/g(
Azanza,(2005(

35. 6/8/17&
35&
Fried$bish$balls$
8.16(×(10
3(
cells/g(
Azanza,(2005(
Fried$milkbish$
1.05(×(10
4(
cells/g(
Azanza,(2005(
Stirgfried$mung$beans$
1.09(×(10
4(
cells/g(
Azanza,(2005(
Fresh$spring$rolls$with$
sautéed$vegetable$billings$
4.41(×(10
5(
cells/g(
Azanza,(2005(

36. 6/8/17&
36&
Chicken$sandwich$
1.56(×(10
5(
cells/g(
Azanza,(2005(
Hamburger$sandwich$
2.73(×(10
5(
cells/g(
Azanza,(2005(
Hotdog$sandwich$
4.37(×(10
6(
cells/g(
Azanza,(2005(
Tuna$sandwich$
1.04(×(10
5(
cells/g(
Azanza,(2005(

37. 6/8/17&
37&
Boiled$rice$
1.68(×(10
5(
cells/g(
Azanza,(2005(
Fried$rice$
2.12(×(10
6(
cells/g(
Azanza,(2005(
Spaghetti$
1.55(×(10
5(
cells/g(
Azanza,(2005(
Rice$noodles$with$thick$shrimp$sauce,$
blaked$smoked$bish,$boiled$eggs$and$
spring$onion$
9.48(×(10
4(
cells/g(
Azanza,(2005(

38. 6/8/17&
38&
Soft$bean$curd$in$light$syrup,$
with$or$without$tapioca$pearls$
7.24(×(10
3(
cells/g(
Azanza,(2005(
Grated$young$coconut$meat$
with$liquid$endosperm$
1.70(×(10
4(
cells/g(
Azanza,(2005(
Tapioca$pearls$and$gelatin$in$
light$syrup$
3.60(×(10
6(
cells/g(
Azanza,(2005(
! (Factors(related(to(growth(
! 'Storage$at$ambient$
! $Improper$cooling$
! $Improper$warm$holding$
How$microorganisms$multiply$
and$eventually$cause$diseases$

39. 6/8/17&
39&
! (Factors(related(to(growth(
! 'Use$of$left$overs$
! $Improper$thawing$
! $Extra$large$quantities$prepared$
How$microorganisms$multiply$
and$eventually$cause$diseases$
! (Factors(related(contamination(
! 'Food$workers$
! $Contaminated$raw$foods$
! $Food$contact$surface$$$$$
$$$$contamination$
How$microorganisms$multiply$
and$eventually$cause$diseases$
Factors$affecting$microbial$
growth$
Potentially$Hazardous$Foods$

40. 6/8/17&
40&
Potentially$Hazardous$Foods$Potentially$Hazardous$Foods$
! Food'in'which'microorganisms'
can'grow'rapidly.'
! Previously(involved(in(
disease(outbreaks.(
! Often'moist,'contain'protein,'
low(acid.'
Food$Temperature$

BASIC

ACIDIC
1.
0
7.0 14.0 4.5
High Acid
limes
pickles
vinegar
mayonnaise
beef
veal
pork
chicken
milk
soda crackers
egg white
2.0 3.0 5.0 6.4 8.5 9.0
Frazier and Westhoff (1988); Jay (2000)
pH$of$some$foods$

41. 6/8/17&
41&
PHF


0.1 0.85 1.0
meats
poultry
soft cheeses
raw bacon
0.98 0.92
0.95
crisp bacon
0.75
flour
candy
0.67
0.50
crackers
Frazier and Westhoff (1988); Jay (2000)
Water$activity$of$some$foods$
! Using'the'rest'room'
! Before'and'after'handling'raw'foods'
! Touching'the'hair,'face'or'body'
! Sneezing,'coughing'or'using'a'handkerchief'
When$to$wash$hands$
! Smoking,'eating,'drinking'
! Touching'aprons'or'clothing'
! Touching'unsanitized'equipment,'work'
surfaces'or'washcloths'
When$to$wash$hands$

42. 6/8/17&
42&
%
 
%
 
Hand$care$for$handlers$
! Gloves'must'never'
be'used'in'place'of'
handwashing.'
Glove$use$
! 'As'soon'as'they'become'''
'''''soiled'or'torn'
! 'Before'beginning'a''
'''''different'task'
! 'At'least'every'4'h''
''''during'continual'use'
Glove$use$ Safe$food$handlers?$

43. 6/8/17&
43&
Accept(Reject(
Setting$criteria$for$acceptance/
rejection$of$raw$materials$
Accept(Reject(
Setting$criteria$for$acceptance/
rejection$of$raw$materials$
! Use(one(cutting(board(
for(fresh(produce(and(
a(separate(board(for(
meats,(`ish(and(
poultry.(
Avoiding$cross$contaminations$
ColdPHolding(HotPHolding(
Holding$foods$safely$

44. 6/8/17&
44&
1 2
Cooling$foods$safely$
3 4
Cooling$foods$safely$
! Poultry$
! 74C,'15's'
! Ground$Meats$
! 68C,'15's'
! Pork,$Beef,$Lamb$
! 63C,'15's'
Cooking$food$at$proper$
temperatures$
! Fish$
! 63Y74C,'15's'
! Leftovers$
! 74C,'15's'
'
Cooking$food$at$proper$
temperatures$

45. 6/8/17&
45&
Serving$foods$safely$Factors$leading$to$foodborne$
illnesses$
Safe(food((
is(a(moving(target…(
The(problem(is(never(solved(
completely(because(change(is(
constant…(
The$Future$ In$the$meantime…$

46. 6/8/17&
46&
The(content(on(this(presentation(is(provided(
to(you(for(your(personal,(educational,(
noncommercial(use,(and(is(provided(for(
informational(purposes(only.((
The(ownership(of(the(photos/`igures/screen(captures(
presented(in(the(following(slides(belong(to(the(respective(
illustrators,(photographers,(artists,(etc.(