jim trostle: pathogens in ecuador

Some adventures in global health and interscalar travel

James Trostle, PhD MPHProfessor of Anthropology

Trinity CollegeFaculty Research Lecture

April 7, 2016

Global health?

Major killers of children under 5 (~6 million deaths in 2015):Respiratory diseases esp. pneumonia,Diarrheal diseases,Malnutrition,Prematurity and birth trauma.

BUT many studies of infectious diseaseare inadequate [lamplight studies!]:

-examine clinics or single villages at one (or at most two) points in time,

-look at individual or village as unit of analysis but not larger scale

-conceptualize risk and behavior as individual(hand washing/water boiling?) or group(municipal water source?) but not interdependent (influence of neighboring town)

Traveling across scales: Some challenges for single-village and life

history accounts

Environmental and social changes:spread across a landscapevary in intensity and velocitycause varied human responsesrequire systems thinking

A challenge for ethnographic accounts

Pathogens move with (inside or on) human bodies, but also move through direct human contact, animal vectors, and environmental reservoirs such as water or food.

A challenge for epidemiological accounts

Epidemiologists glancing ‘upwards’ in scale worry that, by omitting information about the landscape over which epidemiological dynamics unfold, perhaps their models are after all ‘importantly wrong’.

…Likewise, as we peer ‘downwards’, we are increasingly convinced that heterogeneity documented at the level of the individual or gene locus is necessary to capture the broader-scale epidemiological pattern.”

(Matthews and Haydon 2007:763) “Cross-scale influences on epidemiological dynamics: from genes to

ecosystems.”

Chris Jordan

http://www.chrisjordan.com/gallery/rtn/#skull-with-cigarette

Skull With Cigarette, 200798x72"

Depicts 200,000 packs of cigarettes, equal to the # of Americans who die from cigarette smoking every six months.

Disease transmission is individual and communal

Epidemiologic research faces both genetic and sociocultural frontiers: strain typing of pathogens must accompany network descriptions of populations

Road as prompt(But could also be railroads, canals,

pipelines, power lines)

How do roads “work” to influence disease transmission?

Primary, secondary, and tertiary roads

Road construction: product of political decisions & resource availability.

Roads influence interactions between humans, hosts, and environment, leading to pathogen transmission and disease.

How?

- changes in water quality, - Demography, - and networks of human populations, - and availability of goods and services.

HumanEnvironment

Host interaction

PathogensDisease

GoodsServices

Human Population

ForestsWater

Road Construction

Politicaldecisions

Resource availability

New Roads Facilitate Human Movement (Migration Flows)

And resource flows

And Pollution Flows

Environmental Change and Diarrheal Disease in Northern Ecuador

How new roads affect the transmission of diarrheal pathogens in rural coastal EcuadorRoad access unevenly distributed across a region produces

conditions of a natural experimentRelationship between environmental change and disease can

be observed (easily?) and systematically.

Study Design15+ year longitudinal study at village levelTwice yearly case-control studies within

each of 21 [now 24] villages, and commercial center, Borbón.

J. Eisenberg, Epidemiology, Michigan J. Trostle, Anthropology, Trinity

With thanks to: InstitutionsCentro de Biomedicina UCentralUniversidad San FranciscoUniversity of Michigan

*Joseph EisenbergTrinity College

*James TrostleEmory University

Karen LevyMinisterio de Salud Pública*Asociación de Promotores

Field teamBetty CorozoAndrés AcevedoCarmen CampañaKarina PonceJeanneth YépezSimón QuimiJunior MinaAna EstupiñanMaritza RenteríaGeovanny HurtadoDenys TenorioLiliana RequeneJosé Ortiz

The Local Communities

Quito team*William Cevallos*Gabriel TruebaElizabeth FalconiPablo EndaraNadia VeiraRosana SegoviaPatricio RojasMaria Eloisa HashinDeisy ParralesManuel BaldeónNancy Castro

Funding from NIH (NIAID) and NSF (EEID)

Google Earth: Eye altitude 685 miles

Connects villages in three river drainages:

Onzole, Cayapas, Santiago

21 villages, ~4200 inhabitants in June, 2003

36% illiterate (self-report)

89% Afro-Ecuadorian 7% Mestizo<1% Chachi

The 21 villages are categorized by river basin (Santiago, Cayapas, Onzole, Bajo Borbón, road) and remoteness (close, medium, far)

1996-2002 road construction links the S. Colombian border and Andes with the Ecuadorian coast

Causal pathways

Why a road?

Distal political & economic

forces

Assembling evidence about relationships between road-related “development” and disease

DemographyGeography Sociology/anthro (networks)EthnographyEpidemiologyMicrobiology

Environmental Change and Diarrheal Disease in Northern Ecuador: Study Components

Mapping & GIS (once per yr)Villages, houses in relation to roads/rivers, rainfall/temp

4 Network surveys (sociometric)

(2003-4, 2007, 2010, 2013)

Counting & mapping social contacts in all villages

A

B

Study Components

Active disease surveillance (weekly)2003-2007, 2011-14Village cohort study

Case/control study ( twice per year)Risk within villages

Microbiology (throughout) Analysis of marker pathogens

Study ComponentsCensus (once per year)

Population change, migration

Ethnography(throughout)

Behavior, context, meaning, causal inference

Study Components

Mathematical modeling Integrate GIS and disease transmission

models, causal inference

Some of what have we learned (so far)

Pathogen FlowsPerson-to-environment transmission (Sanitation)

Pathogen Flows

Hygiene

Within household person-to-

person transmission

Water quality

Environment-to-person

Example 1: Village remoteness (increased cost and time of

transport) influences the spread of pathogens and disease

Close

Medium

Remote

Remoteness and Disease

E. coli

(Bacteria)

Rotavirus

(Virus)

Giardia

(Protozoa)

Diarrhea

(All Causes)

Remote 1.00 1.00 1.00 1.00

Medium 3.0 1.3 1.2 1.8

Close 3.9 4.1 1.6 1.8

Continuous 8.4 4.0 1.9 2.7

(Estimates by village were adjusted for age of individual,

population of village, sanitation level, and climate)

Eisenberg et al., PNAS, 2006

Demographic changes

Tendencies by remoteness:More mestizos in near communities (12%) than far ones(4%)

Shorter duration of village residence in near communities(13 years) than far ones (21 years)

A

B

Spatial Layout of a Road (A) and Remote (B) Village

Food-sharing Networks in a Road (A) and Remote (B) village (2004)

Trostle et al. Epidemiology 2008

A B

Social Support Networks [with whom can you discuss important things?] in a Road (A) and Remote (B) village (2007)

Village A: 306 nodes11 components + isolates

Village B: 327 nodes5 components + isolates

A B

Causal Model of Transmission Potential

From close to medium to remote villages

0

10

20

30

40

50

60

70

0.000 0.050 0.100 0.150 0.200 0.250

Remoteness

% L

eavi

ng V

illag

e

Decreased reintroduction of pathogens from outside of

regions?

Increased social solidarity and political strength?

0.002.004.006.008.00

10.0012.00

0.000 0.050 0.100 0.150 0.200 0.250

Remoteness

Deg

ree

Case Study 1A: The Complex Relevance of Social Networks to

Disease TransmissionHuman systems (food/economic resource/social

support networks) create different environments for the possible transmission of pathogens.

Food-borne pathogens may spread more readily in dense food-sharing networks; but host resistance and prevention may be higher in dense social support networks.

These (social) environments vary with remoteness.

(Trostle et al. 2008, Zelner et al. 2012)

“Ask when – not just whether - it’s a risk: How regional context influences local causes of diarrheal disease” (Goldstick et al, AJE 2014)

– Four years of active surveillance data across 21 villages

– Markov chain model where state of village k (high, medium or low diarrheal rates) at time t depends on the state of the 21 villages at time t-1.

Villages are weighted using a gravity model (distance and size)

Ecological Perspective: Regional TransmissionCase study 2

The incidence of diarrhea in neighboring villages

affects the risks in your village

Cas

es o

f di

arrh

ea

When neighboring villages

have little diarrhea, treating

the water is beneficial

Water treatment

Neighbor village

Your village

Neighbor village

Lots of diarrhea

Little diarrhea

Water treatment

The incidence of diarrhea in neighboring villages

affects the risks in your village

When neighboring villages

have lots of diarrhea, treating

the water is not as effective

Cas

es o

f di

arrh

ea

Neighbor village

Your village

Neighbor village

Lots of diarrhea

Little Diarrhea


• Risk factors are often characterized as static– But they may vary by social and biological

contexts– Need to shift question from: ‘is variable X a

risk?’ to ‘when (under what conditions ) is variable X a risk?’

• Environmental transport vs. human movement

Ecological Perspective: ClimateCase study 3

Social and environmental contexts modify the effect of extreme rainfall on diarrhea incidence in Northern Coastal Ecuador (Carlton et al, 2013)

Four years of active surveillance data: 21 villagesFour years of climate data: 4 villagesEnvironmental variables:

Climate (total rainfall)Infrastructure (water + sanitation)Behavior (hygiene)Social capital/cohesion


0

2

4

6

8

10

12

14

Dia

rrhe

a in

cide

nce

(cas

es p

er 1

,000

per

son-

wee

ks)

02/04 05/04 08/04 11/04 02/05 05/05 08/05 11/05 02/06 05/06 08/06 11/06 02/07 05/07

�Outcome: DiarrheaWeekly visits to households over 4 years


• Exposure– Extreme rainfall: 90th

percentile over 4 year period• Contextual variable

– 8-week total rainfall

0

50

100

150

200

Max

imum

1-d

ay ra

infa

ll in

1 w

eek

(mm

)

02/04 05/04 08/04 11/04 02/05 05/05 08/05 11/05 02/06 05/06 08/06 11/06 02/07 05/07

0

200

400

600

800

1000

1200

1400

Tota

l rai

nfal

in th

e pr

evio

us 8

wee

ks (m

m)

02/04 05/04 08/04 11/04 02/05 05/05 08/05 11/05 02/06 05/06 08/06 11/06 02/07 05/07

Ecological Perspective: Climate and RainfallCase study 3

Conclusion/InterpretationWater flows

Under dry conditions extreme rain events increases riskFlushes contamination buildup from soil to water

Under wet conditions extreme rain events decrease riskFurther dilutes pathogens

Behavior flowsWater treatment can counteract increases in risk during dry period Water treatment is required to realize protective effect during wet periods.

Where we’re going

How do social dynamics interact with hydrodynamics to drive patterns of waterborne diseases?

• Based on this understanding, what are the consequences of a more variable and changing climate?

Data: GI illness data, surface water quality/dynamics, social structure/dynamics

In-channel Flows

Overbank Flows Runoff Hydrological Networks

Social Cohesion

Socio-behavioral Dynamics

Social Transitions

Social Networks

Village 1 Village 2

Mathematical epi model

Hydrological model Social vulnerability model

Moss et al. Nature 2010

Components of the social environment influencing disease risk

• Demographic changes– Migration– Movement patterns

• Social cohesion– Social network degree

• Outside contacts• Social capital• Infrastructure

– Sanitation– Hygiene– Water projects

Vulnerability is the degree to which a system is susceptible to, or unable to cope with, adverse effects of climate change

Because vulnerability is a dynamic process, a systemsapproach is needed

Feedback through household proximity to river

17 feet

2003, 2010

Models, including agent-based simulations, can be used to study systems

• Can incorporate & investigate: • Heterogeneity and

stochasticity• Population-level (emergent)

outcomes from individual-level behaviors and objectives

• Multiple scales and context-specific details

• Our model analyses will explore:

• Relative impact of different climate conditions on adaptation decision-making

• Relationship between vulnerability and disease outcomes

• Alternative functions for combining exposure, sensitivity, and adaptive capacity

• Relationship between social environment and disease transmission

• For example, Human movement patterns, environmental cues (e.g., flood or drought conditions) and diarrheal disease

Some methodological challenges:Different rhythms of data collection (periodicity and duration of measurement) Different rhythms of analysis (movement and serotype analysis)Challenge of “thick description” of ecology or systems

Are there necessary limits to interdisciplinary work of this type? What are they? cost?complexity?time?

Conclusions

Natural experiments as opportunity for many disciplines

Road as transect and system provocation/perturbation

Many types/levels of “social” dataChallenges of measuring diverse flowsChallenges of integrating methods and

disseminating results

For more information:www.sph.umich.edu/scr/ecodess

OR Google: Ecodess

Local presentationsPresentations/discussions for: Village assemblies in all study villagesLocal hospital and community epidemiology

program employees (Borbon)Provincial Ministry of Health (Esmeraldas)National Ministry of Health (Quito)Public and private universities in Quito (FLACSO,

U Central, USFQ)

Degree training (* = Ecuador)2015. Stephanie Garcia. “Unidos Somos Más.”An exploration of social cohesion as a time-dependent variable in San Miguel and Telembí,

two Afro-Ecuadorian villages in Esmeraldas, Ecuador. BA Honor’s Thesis, Anthropology.2011. Jennifer Jimenez, Cathya Solano (Independent Studies) Anthropology, Trinity College.2009. Katherine J. Connors. Environmental Change and Infectious Disease: How Road Access Affects the Transmission of Dengue Fever in

Rural Ecuador. MPH Thesis, Epidemiology. University of Michigan.2008. Cristina S. Wheeler Castillo. Measurement of Socioeconomic Position and its Health Implications in Rural Ecuador.

BA thesis in International Health Studies, Trinity College. (Winner of the Grossman Senior Research Prize for Global Studies.)2008. Owen Solberg. Population Genetic Diversity of Two Pathogens and the Role of Balancing Selection in HLA Immunogenetics.Chapter 1:

Molecular epidemiology of group A rotavirus in Ecuador. Ph.D., Integrative Biology . U.C. Berkeley.*2007. Rosana Segovia. Evidence of Horizontal Gene Transfer of Antibiotic Resistance Genes in Communities with Limited Access to Antibiotics

MS Thesis, Universidad San Francisco de Quito. * 2007. Eloisa Hasing. Sudden Replacement of Rotaviral Genotype G9 in Ecuador. MS Thesis, Universidad San Francisco de Quito. * 2007. Patricio Rojas. Genotypes of Enterotoxigenic E. coli in Ecuadorian Remote Communities.

MS Thesis, Universidad San Francisco de Quito. * 2007. Dimitri Kakabadse. Conjugative Transference of Antibiotic Resistance in E. coli Isolates from Esmeraldas Province

BS Thesis, Universidad San Francisco de Quito. 2007. Karen Levy. Environmental Drivers of Water Quality and Waterborne Disease in the Tropics with a Particular Focus in Northern Coastal

Ecuador. Ph.D. in Environmental Science, Policy, and Management. U.C. Berkeley.2007. Marylin Rodriguez. Migración urbana en la costa de Ecuador: Tradiciones de salud en transición. (Urban migration on the

Ecuadorian coast: Health traditions in transition.)

BA honor's thesis, Trinity College, International Studies and Hispanic Studies.* 2006. Pablo Endara. High Prevalence of P[8]G9 Rotavirus in Remote Coastal Communities of Ecuador.

MS in Microbiology, Universidad San Francisco de Quito.* 2006. Nadia Vieira. High prevalence of Enteroinvasive Escherichia coli isolated in a remote region of northern coastal Ecuador.

MS in Microbiology, Universidad San Francisco de Quito.* 2006. Patricio Bueno. Analisis Microbiologico del Agua de la Parroquia Borbon, Canton Eloy Alfaro y su Asociacion con la Enfermedad

Diarreica. BS, Universidad San Francisco de Quito.2005. Sarah Bates. The relevance of social and geographic structures to disease transmission in rural Ecuador.

MS in Health, Environment, and Development, U.C. Berkeley School of Public Health* 2005. Sonya Ontoneda. MS in Microbiology, Universidad San Francisco de Quito.

2004. Betsy Cowan. The Social World of a Road in Northwest Ecuador. B.A. Honor’s Thesis, Anthropology, Trinity College.

Social connectedness can inhibit disease

transmission: Social organization, cohesion, village

context and infection risk in rural Ecuador. Jon Zelner,

James Trostle, Jason Goldstick, James House, and Joseph NS Eisenberg

Media outreach (to newspapers, television, internet) www.sph.umich.edu/scr/ecodess/home.php

jim trostle: pathogens in ecuador

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