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    Figure 1.

    Study sites and natural geographic regions (desert, highland, and jungle) of Peru. Small dots and squares with two capital letters represent study sites (BP, Buen Villa Pastor; SC, San Carlos; VC, Vichaycocha; QC, Quilcas; PM, Las Pampas; HU, Huascahura; SJ, San Jeronimo; CC, Cerro Colorado; SA, Sachaca). Large dots represent major cities near the study sites. The square represents the capital city of Lima.

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    Figure 2.

    Prevalence of positive tuberculin skin test reaction by altitude and type (urban or rural) of the community. R, rural community; U, urban community. GEE model was used to account for family clustering.

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COMPARISON OF ALTITUDE EFFECT ON MYCOBACTERIUM TUBERCULOSIS INFECTION BETWEEN RURAL AND URBAN COMMUNITIES IN PERU

MAYUKO SAITODepartment of International Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland; Asociación Benéfica, Proyectos en Informática, Salud, Medicina y Agricultura (A. B. PRISMA), Lima, Peru; Department of Microbiology, Universidad de Cayetano Heredia, Lima, Peru; US Military HIV Research Program and the Henry M. Jackson Foundation, Rockville, Maryland

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WILLIAM K. PANDepartment of International Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland; Asociación Benéfica, Proyectos en Informática, Salud, Medicina y Agricultura (A. B. PRISMA), Lima, Peru; Department of Microbiology, Universidad de Cayetano Heredia, Lima, Peru; US Military HIV Research Program and the Henry M. Jackson Foundation, Rockville, Maryland

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ROBERT H. GILMANDepartment of International Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland; Asociación Benéfica, Proyectos en Informática, Salud, Medicina y Agricultura (A. B. PRISMA), Lima, Peru; Department of Microbiology, Universidad de Cayetano Heredia, Lima, Peru; US Military HIV Research Program and the Henry M. Jackson Foundation, Rockville, Maryland

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CHRISTIAN T. BAUTISTADepartment of International Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland; Asociación Benéfica, Proyectos en Informática, Salud, Medicina y Agricultura (A. B. PRISMA), Lima, Peru; Department of Microbiology, Universidad de Cayetano Heredia, Lima, Peru; US Military HIV Research Program and the Henry M. Jackson Foundation, Rockville, Maryland

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SAPNA BAMRAHDepartment of International Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland; Asociación Benéfica, Proyectos en Informática, Salud, Medicina y Agricultura (A. B. PRISMA), Lima, Peru; Department of Microbiology, Universidad de Cayetano Heredia, Lima, Peru; US Military HIV Research Program and the Henry M. Jackson Foundation, Rockville, Maryland

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CHRISTOPHER A. MARTÍNDepartment of International Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland; Asociación Benéfica, Proyectos en Informática, Salud, Medicina y Agricultura (A. B. PRISMA), Lima, Peru; Department of Microbiology, Universidad de Cayetano Heredia, Lima, Peru; US Military HIV Research Program and the Henry M. Jackson Foundation, Rockville, Maryland

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SIMON J. TSIOURISDepartment of International Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland; Asociación Benéfica, Proyectos en Informática, Salud, Medicina y Agricultura (A. B. PRISMA), Lima, Peru; Department of Microbiology, Universidad de Cayetano Heredia, Lima, Peru; US Military HIV Research Program and the Henry M. Jackson Foundation, Rockville, Maryland

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D. FERMÍN ARGÜELLODepartment of International Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland; Asociación Benéfica, Proyectos en Informática, Salud, Medicina y Agricultura (A. B. PRISMA), Lima, Peru; Department of Microbiology, Universidad de Cayetano Heredia, Lima, Peru; US Military HIV Research Program and the Henry M. Jackson Foundation, Rockville, Maryland

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GABRIELA MARTINEZ-CARRASCODepartment of International Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland; Asociación Benéfica, Proyectos en Informática, Salud, Medicina y Agricultura (A. B. PRISMA), Lima, Peru; Department of Microbiology, Universidad de Cayetano Heredia, Lima, Peru; US Military HIV Research Program and the Henry M. Jackson Foundation, Rockville, Maryland

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The mechanism of high altitude effect on tuberculosis (TB) infection has not been fully established. We previously reported a lower positive tuberculin skin test (TST) prevalence in high altitude villages compared with sea level communities in Peru. In this study, four additional communities were tested to assess whether decreased TB transmission was also in urban environments at high altitude. TST results from 3,629 individuals in nine communities were analyzed using generalized estimating equations to account for community clustering. Positive TST prevalence was not significantly different between the urban highland and the urban non-highland communities after adjusting for age, household contacts with a TST-positive person or a TB case, and presence of a Bacillus Calmette-Guérin vaccination scar. The effect of population concentration and increased contact with active TB overwhelmed the protective effect of altitude in urban highlands. Highland cities require the same preventive efforts against TB as non-highland communities.

INTRODUCTION

Worldwide, tuberculosis (TB) affects eight million people annually, yet 95% of TB cases and 98% of TB deaths occur in resource-limited countries.1 TB and multi-drug–resistant Mycobacterium tuberculosis (MTB) have re-emerged because of increases of human immunodeficiency virus (HIV) infection in developing countries.2

Peru is one of the resource-limited countries in which TB is endemic. The estimated prevalence of active TB in Peru is 233 cases per 100,000 inhabitants in 2004,3 despite a low prevalence of HIV infection of 0.5% among adults.4

In a previous study, we observed a lower TB transmission in high altitude rural communities compared with both urban and rural sea level communities in Peru.5 This study tested four additional communities at varying altitudes to examine the effects of high altitude and urban environment on tuberculin skin test (TST) positivity.

MATERIALS AND METHODS

Study design.

A previous study sampled five study sites, two rural highland, one urban lowland, and two rural lowland sites,5 but did not include urban highland communities. In this study, two urban highland communities and two urban mid-highland communities were added to determine if positive TST prevalence decreased with altitude in urban highland communities

Study sites.

Nine communities were studied (Figure 1). Five of these have been described in detail in a previous study5. Two urban non-highland (altitude < 3,000 m) shantytowns, Sachaca, and Cerro Colorado, and two highland (altitude ≥ 3,000 m) peri-urban shantytowns, San Jeronimo and Huascahura, were newly studied.

Rural highland communities.

Quilcas is a rural Andean village with ~1,280 inhabitants located 45 km from Huancayo (population: 327,000)5. Vichaycocha is a rural Andean village with ~520 inhabitants located 150 km northeast of the capital city of Lima.5

Urban highland communities.

Huascahura is a peri-urban village with ~1,760 inhabitants located near Ayacucho (population: 140,500). San Jeronimo is a peri-urban shantytown with 19,120 habitants located in the southern part of the center of Cusco (population: 342,000).

Rural non-highland communities.

Buen Villa Pastor is a rural jungle village with ~270 inhabitants in the Amazon basin.5 San Carlos is a rural jungle village with 176 inhabitants similar to Buen Villa Pastor.5

Urban non-highland communities.

Las Pampas is an urban desert shantytown with > 40,000 inhabitants in southern Lima.5 Sachaca is an urban town with 16,570 inhabitants near the southern part of Arequipa, the second largest city of Peru (population: 677,000). Cerro Colorado is an urban shanty-town (population: 70,000) located in the northern area of Arequipa.

Residents in the shantytowns are impoverished, earning money from temporary small businesses, selling seasonal agricultural products, or working for construction companies. Their houses have few windows and are made of stones or adobe. Populations living in these nine sites are nearly all Mestizo, descendants of mixed European and Native American ancestry. Climate in the highlands is relatively dry and cold, with a rainy season lasting for 3 mo/yr. The jungle areas are humid. The geographic characteristics of each site are shown in Table 1 and Figure 1.

Field operations.

The participants in Vichaycocha were obtained from a health post, and the data do not include all family information.5 The sample households were chosen in Quilcas and Las Pampas from computerized census data using random sampling function of FoxPro ver.2.6 (Microsoft, Redmond, WA), whereas the whole village population was invited to participate in San Carlos and Buen Villa Pastor. In Sachaca, Cerro Colorado, Huascahura, and San Jeronimo, a part of the community was selected, and all houses were included.

A household was defined as persons who share common living space such as a kitchen, living room, and bathroom. All family members excluding infants < 6 months of age and people who were temporally staying in the house (< 6 months) were invited to the study. Written informed consent was obtained from all adult participants (≥ 18 years of age) and from the parents or guardians of children. All participants were interviewed with structured questionnaires regarding recent (within 5 years) exposure to active TB cases and general conditions of health.

Trained field workers performed the TST using an intra-dermal injection of 5 tuberculin units (Tubersol; Connaught Laboratories, Ontario, Canada) in 0.1 mL on the volar surface of the forearm. Tuberculin vials (1 mL) were kept refrigerated and carried in a cooler box with ice packs. Induration produced by injections was measured 48–72 hours after administration using the pen method.6 Induration size ≥ 10 mm was considered to be TST positive, according to the Peruvian Ministry of Health7 and American Thoracic Society recommendations for people born in countries with high prevalence of TB.8 Although different field workers worked in different study sites, all fieldworkers underwent standardized training for reading the TST by an experienced research nurse, and the field work was supervised by one of the authors (M.S.). Participants with a positive TST were evaluated for evidence of active TB as described in the previous study.5

This study was approved by the ethical review boards of Asociación Benéfica PRISMA, Lima, Peru, and the Johns Hopkins Bloomberg School of Public Health, Baltimore, MD.

Statistical analysis.

Demographic characteristics of the study population and TST results were compared among study sites. Differences in continuous variables were evaluated by Kruskal-Wallis and Mann-Whitney U tests. χ2 tests were used to test differences in categorical or binary variables. Educational level was categorized as no education (< 6 years), primary education (6 years completed), and secondary education (≥ 12 years completed). Body mass index (BMI) was calculated for six communities (data in San Carlos, Huascahura, and Vichaycocha were not available). The positive TST prevalence was compared between rural highland, rural non-highland, urban highland, and urban non-highland communities using a Wald χ2 test computed from a generalized estimating equations (GEE) model to account for the family clustering effect.9

Characteristics of the study population were compared between individuals living in the highland (≥ 3,000 m) and non-highland (< 3,000 m) communities. Populations were also divided into rural or urban based on distance and ease of travel to the city center. Additional background information such as experience of living with other person with active TB, presence/absence of Bacillus Calmette-Guérin vaccination (BCG) scar, and living in an urban area or rural area was also compared. The Wald χ2 test computed from GEE was used to test differences to account for community clustering.

To find factors associated with positive TST prevalence, univariate analyses were performed on the entire study sample for sex, age, history of living with a person with active TB, presence/absence of BCG scar, number of people per household, and living in rural highland compared with living in urban highland, living in rural non-highland, and living in urban non-highland. Educational level and BMI were analyzed only for adults ≥ 18 years of age. Multiple analyses were performed on 3,161 people (1,466 adults and 1,695 children) from eight communities except Vichaycocha, because data from Vichaycocha lacked household information and was thus excluded from the regression model. Model estimation was performed using GEE to account for community clustering. Adjusted odds ratios (AORs) were compared between each of the different types of communities (rural highland, rural non-highland, urban highland, and urban non-highland).

Non-parametric tests, χ2 test, and GEE models for family clustering were performed using Stata 8.0 (Stata Corp., College Station, TX). GEE models for community clustering were computed using SAS statistical software 9.1 (SAS Institute, Cary, NC).

RESULTS

Distribution of demographic characteristics.

In this study, data from a total of 3,629 people from the nine sites were analyzed. The number of households, participants, and the participation rates to the target population are shown in the Table 1. Median age in years, proportion of the child population, educational level, BMI, and the median number of people per household were significantly different among the study sites (Table 1). When we compare the background characteristics among the study population from the four highland communities and five non-highland communities, there was no significant difference in the demographic factors such as sex, age, living with other person with active TB or not, educational level, BMI, presence/absence of a BCG scar, number of person within the household, and living in an urban area or rural area.

Positive TST prevalence.

Overall positive TST prevalence in the study population was 21.1% (95% confidence interval [CI]: 19.7–22.3). The lowest positive TST prevalence was found in Vichaycocha (6%, rural highland), and the highest prevalence was in Buen Villa Pastor (33%, rural non-highland; Table 1). Positive TST prevalence was lower in rural highland communities compared with rural non-highland communities (OR = 0.14, P < 0.001); however, there was no significant difference between urban highland and urban non-highland communities (OR = 0.92, P = 0.500; Figure 2). In highland communities, positive TST prevalence was significantly higher in urban communities than in rural communities (OR = 2.84, 95% CI: 2.00–4.03, P < 0.001). In contrast, in the non-highland sites, positive TST prevalence was higher in rural than urban communities (OR = 1.43, 95% CI: 1.09–1.89, P = 0.011; Figure 2).

Low TST positive prevalence in rural highland.

In the multiple regression analysis, the positive TST prevalence remained significantly lower in the rural highland communities than in the urban highland, rural non-highland, and urban non-highland sites after adjusting for sex, age, living with another person with a positive TST, having lived with another person with active TB, having a BCG scar, and number of person within the household (Table 2). This trend was constant when adults ≥ 18 years of age and children < 18 years old were analyzed separately (Tables 3 and 4).

Comparison of altitude effect between rural and urban communities.

When we compared between rural non-highland and rural highland communities, the non-highland population had a significantly higher positive TST prevalence than the highland population (AORs in total population, adults, and children were 5.16, 5.50, and 5.75, respectively; Tables 2–4). In contrast, among the urban communities, the differences between non-highland and highland were not significant in the total population (difference in the AOR = 1.12, 95% CI: 0.95–1.33) and the adult population (difference in the AOR = 1.13, 95% CI: 0.98–1.30). In the children, however, the AOR of positive TST prevalence was lower in the non-highland community group than in highland group (difference in the AOR = 0.82, 95% CI: 0.71–0.94).

Comparison of positive TST prevalence between rural and urban communities.

The positive TST prevalence was significantly higher in urban communities than in rural communities in the highlands (difference in the AOR = 3.52, 95% CI: 3.03–4.09), whereas in the non-highland environment, the positive TST prevalence was higher in rural communities than in the urban communities. The difference in AOR of these non-highland communities was significant for the whole population (1.30, 95% CI: 1.14–1.49) and adults (1.45, 95% CI: 1.27–1.66), but not for children (1.30, 95% CI: 0.81–2.09).

Other factors associated with positive TST results.

In adults, male sex, older age group (≥ 32 years old), living with another person with a positive TST, having lived with another person with active TB, and having a BCG scar were all associated with a positive TST in both univariate and multiple regression analyses (Table 3). In children, univariate analysis indicated all variables were positively associated with a positive TST except male sex (Table 3). After adjusting for all variables, having contact with a family member with active TB and the number of persons within the same family were not associated.

DISCUSSION

The protective effect of high altitude on positive TST prevalence in a rural highland population, found in a previous study, was nearly completely overcome in urban highland populations. Crowding and increased contact with persons with active TB infection are the probable causes for the reversal of the low transmission rates of TB infection that is present in rural highland areas. Rural highland villages also experience little migration into their population from the lowlands where TB disease is common.

Using GEE to estimate model parameters to account for community clustering effects, the effects of associated factors were tested. High altitude had strong association with a decreased rate of TST positivity even after adjusting for age, household active TB contacts, household positive TST contacts, BCG vaccination status, and community clustering. The finding of greater TB infection risk in rural versus urban at low altitude, with the opposite finding at high altitude, may be caused by the high humidity present in the jungle and the relative lack of health care facilities.

Limitations of this study are that the number of sites was not large enough to show if there was a linear or threshold protective effect of high altitude in rural areas. Even though we accounted for the effect of contact with a known active TB patient or another person with a TST-positive result in the same household, it was not possible to account for the risk of acquiring MTB infection from visitors, temporal immigrants to the community, or unknown contacts. The non-significant effect of an active TB contact (AOR = 2.4) in children was most likely caused by a small sample size for this variable. In addition, the relatively wide CIs for the adult TST prevalence data are also probably related to a low sample size in each community.

The mechanism of the high altitude effect on TB disease or MTB infection has not been fully established. The number of studies on this topic decreased after the discovery of the anti-TB drugs in the 1940s. Altitude effects on TB transmission rates have only been examined in one previous study in Darjeeling10 reported that positive TST prevalence was decreased in villages above 1,000 m compared with those below this altitude. That study, however, did not control for confounding factors. In terms of TB disease, which our study did not examine, two recent studies from Mexico showed an inverse relationship between altitude and TB disease morbidity11 and mortality.12 Although the Mexican findings of an association between TB disease and altitude could be caused by a decreased severity of the TB disease at high altitude, an effect of altitude on MTB transmission is equally likely.

There are several mechanisms by which MTB infection might be prevented in high altitude climate, such as lower oxygen tensions13 or stronger exposure to ultraviolet (UV) light, which may inhibit MTB growth.14 However, houses in the highland have relatively small and few windows; therefore, UV rays may not reach inside houses, where transmission is most likely to occur. The dry climate in high altitude may increase the susceptibility of Mycobacterium to UV light,15 reducing TB transmission. Further detailed studies are needed to determine which mechanism(s) are primarily responsible for the decreased transmission of TB in the highlands.

The protective effect of high altitude on MTB infection found in rural highland communities was not found in urban highland communities. Assuming that high TB transmission rates reflect high rates of active TB, urban highland communities will require the same measures against TB as non-highland communities.

Table 1

Study site description, demographic characteristics of the study population, and positive TST prevalence

DesertTropical jungleMid-highlandHighland
CommunityPMBPSCSACCHUSJQCVC
PM, Las Pampas; BP, Buen Villa Pastor; SC, San Carlos; SA, Sachaca; CC, Cerro Colorado; HU, Huascahura; SJ, San Jeronimo; QC, Quilcas; VC, Vichaycocha.
* Households are randomly selected.
†NA, not available. Participation in the study was requested at the health post.
‡P < 0.05.
§Weight and height were not available in San Carlos, Huascahura, and Vichaycocha; [range] = percentile range.
¶95%CIs were corrected for family clustering effect using generalized estimating equations (GEE) model.
Altitude (meter)1401101102,2402,6503,0003,2403,3303,500
Urban/ruralUrbanRuralRuralUrbanUrbanUrbanUrbanRuralRural
Number of households participated307*4031776856117100*NA†
Number of participants tested (% targeted)1238 (85)186 (70)149 (85)308 (81)226 (72)241 (80)458 (81)453 (67)370 (72)
Female/male ratio1.21.01.01.11.51.31.11.11.1
Median age in years‡151915182017161316
Number of children < 18 years old (%)‡690 (56)89 (48)80 (54)151 (49)104 (46)122 (51)251 (55)266 (59)189 (51)
Education level in adults‡
    No education (%)40/544 (7)8/96 (9)6/66 (9)26/148 (17)23/122 (19)61/89 (51)70/207 (34)27/187 (15)21/172 (12)
    Primary (%)217/544 (40)57/96 (59)43/66 (65)81/148 (55)40/122 (33)36/89 (30)69/207 (33)111/187 (59)105/172 (61)
    Secondary or more (%)287/544 (53)31/96 (23)17/66 (26)41/148 (28)59/122 (48)22/89 (19)68/207 (33)49/187 (26)46/172 (27)
BMI of adults [range]‡§24 [22–27]23 [21–25]24 [22–27]25 [23–28]24 [22–27]23 [21–25]
Median number of people in the household5 [4–6]5 [4–8]5 [4–7]5 [4–6]4 [3–5]5 [3.5–7]5 [3–6]4 [3–6]NA†
TST positive prevalence(%) [95%CI]‡¶25 [23–28]33 [26–42]31 [25–38]26 [22–32]22 [17–29]23 [17–29]24 [20–29]7 [4–10]6 [4–9]
Table 2

Crude and adjusted ORs for TST positivity in total study popuation*

VariablesORAOR95% CI
* OR and AOR were computed using GEE model. AOR was adjusted for all variables in the model. Missing data in the regression analysis inlcuded 370 individuals in Vichaycocha, 80 people without BCG scar data, and 18 lacked information on their TB contact status.
† P < 0.05.
‡ The categories with Reference described the baseline group for OR calculation.
Male sex1.091.34†[1.05–1.72]
Age group (in years)
    0–6Reference‡Reference
    7–174.76†4.75†[2.43–9.28]
    18–3116.08†19.91†[9.40–42.17]
    ≥ 3233.37†42.17†[22.52–78.96]
Living with other person with a positive TST1.30†1.84†[1.42–2.38]
Living or has lived with other person with active TB1.72†1.81†[1.29–2.56]
Presence of BCG scar1.88†1.77†[1.36–2.30]
Number of person within the household0.980.99[0.95–1.04]
Living in rural highlandReferenceReference
Living in urban highland4.25†3.52†[3.03–4.09]
Living in rural non-highland6.60†5.16†[4.72–5.63]
Living in urban non-highland4.63†3.96†[3.48–4.37]
Table 3

Crude and adjusted ORs for TST positivity in adult population (≧ 18 years old)*

VariablesORAOR95% CI
* OR and AOR were computed using GEE model. AOR was adjusted for all variables in the model. BMI data were not available from 369 adults in three communities (Vichaycocha, Huascahura, and San Carlos) and 16 adults from other communities. Fifty-one adults were missing one of the covariates.
†P < 0.05.
‡The categories with Reference describe the baseline group for OR calculation.
Male sex1.65†1.65†[1.30–2.10]
Age group (in years)
    18–31Reference‡Reference
    ≥ 322.00†2.13†[1.51–3.56]
Living with other person with a positive TST1.74†1.69†[2.33–1.23]
Living or has lived with other person with active TB1.58†1.54†[1.23–1.92]
Educational level
    No educationReferenceReference
    Primary0.991.28[0.90–1.81]
    > Secondary1.131.12[0.87–1.62]
BMI by 25th percentile
    < 22ReferenceReference
    22–23.90.981.01[0.58–1.35]
    24–26.40.910.86[0.55–1.31]
    ≥ 26.51.140.90[0.74–1.35]
Presence of BCG scar2.04†1.64†[1.27–2.04]
Number of person within the household1.61.00[0.94–1.07]
Number of person within the household1.061.00[0.94–1.07]
Living in rural highlandReferenceReference
Living in urban highland4.09†3.36†[3.02–373]
Living in rural non-highland8.13†5.50†[4.96–6.11]
Living in urban non-highland4.59†3.79†[3.39–4.24]
Table 4

Crude and adjusted ORs for TST positivity in children (0–17 years old)*

VariablesORAOR95% CI
* OR and AOR were computed using GEE model. AOR was adjusted for all variables in the model. One hundred eighty-nine children from Vichaycocha, 11 children without the data on BCG scar, and 47 children without the data of contact with patients with active TB were excluded from the multiple regression model.
† The categories with Reference describe the baseline group for OR calculation.
‡ P < 0.05.
Male sex1.061.03[0.70–1.53]
Age group (in years)
    0–6Reference†Reference
    7–174.17‡4.56‡[2.37–8.77]
Living with other person with a positive TST4.16‡3.45‡[1.63–7.31]
Living or has lived with other person with active TB3.37‡2.38[0.91–6.23]
Presence of BCG scar3.04‡3.58‡[1.96–6.56]
Number of person within the household1.09‡1.01[0.96–1.07]
Living in rural highlandReferenceReference
Living in urban highland9.16‡5.43‡[4.21–7.00]
Living in rural non-highland8.12‡5.75‡[3.27–10.12]
Living in urban non-highland7.77‡4.43‡[3.69–5.31]
Figure 1.
Figure 1.

Study sites and natural geographic regions (desert, highland, and jungle) of Peru. Small dots and squares with two capital letters represent study sites (BP, Buen Villa Pastor; SC, San Carlos; VC, Vichaycocha; QC, Quilcas; PM, Las Pampas; HU, Huascahura; SJ, San Jeronimo; CC, Cerro Colorado; SA, Sachaca). Large dots represent major cities near the study sites. The square represents the capital city of Lima.

Citation: The American Journal of Tropical Medicine and Hygiene Am J Trop Med Hyg 75, 1; 10.4269/ajtmh.2006.75.49

Figure 2.
Figure 2.

Prevalence of positive tuberculin skin test reaction by altitude and type (urban or rural) of the community. R, rural community; U, urban community. GEE model was used to account for family clustering.

Citation: The American Journal of Tropical Medicine and Hygiene Am J Trop Med Hyg 75, 1; 10.4269/ajtmh.2006.75.49

*

Address correspondence to Robert H. Gilman, Department of International Health, The Johns Hopkins School of Pubic Health, 615 North Wolfe Street, Room W5515, Baltimore, MD 21205. E-mail: rgilman@jhsph.edu

Authors’ addresses: Mayuko Saito, Will K. Pan, and Robert H. Gilman, Department of International Health, The Johns Hopkins School of Public Health, 615 North Wolfe Street, Room W5515, Baltimore, MD 21205, E-mails: msaito@jhsph.edu and rgilman@jhsph.edu. Christian T. Bautista (present affiliation), Department of Epidemiology and Threat Assessment, The US Military HIV Research Program, and the Henry M. Jackson Foundation, 1 Taft Court, Suite 250, Rockville, MD 20850, E-mail: cbautista@hivresearch.org. Sapna Bamrah, Christopher A. Martín, Simon J. Tsiouris, D. Fermín Argüello, and Gabriela Martinez-Carrasco, Asociación Benéfica, Proyectos En Informática, Salud, Medicina y Agricultura (A.B. PRISMA), Carlos Gonzales 251, Urb. Maranga, San Miguel, Lima 32, Peru.

Acknowledgments: We thank L. Cabrera, R. Montoya, and P. Maguiña for study coordination, M. Varela for data management, and A. Griffin, J. B. Phu, D. Sarah, and A. Sebastian for technical support. We also thank the communities of Quilcas, Vichaycocha, Las Pampas de San Juan de Miraflores, San Carlos, Buen Villa Pastor, Sachaca, Cerro Colorado, San Jeronimo, and Huascahura for cooperation. Portions of the data contained in this manuscript were presented at the ASTMH 53th Annual Meeting, Miami Beach, Florida, November 7–11, 2004.

Financial support: These studies were supported by D43 TW07646-5 Tutorial in Tropical Health at JHU/Peru Overseas Site NIH/NIAID, D43 TW066581 Infections Diseases Training Program in Peru-Global Research Fund DHHS/Fogarty International, and Research Support Grant from St. Luke’s Life Science Institute.

Disclaimer: The opinions and assertions made by the authors do not reflect the official position or opinion of the US Department of the Army or of any of the other organizations listed.

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