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Logo of nihpaAbout Author manuscriptsSubmit a manuscriptHHS Public Access; Author Manuscript; Accepted for publication in peer reviewed journal;
Am J Public Health. Author manuscript; available in PMC 2014 June 19.
Published in final edited form as:
PMCID: PMC3478018

Effects of the 1997–1998 El Niño Episode on Community Rates of Diarrhea



To improve our understanding of climate variability and diarrheal disease at the community level and inform predictions for future climate change scenarios, we examined whether the El Niño climate pattern is associated with increased rates of diarrhea among Peruvian children.


We analyzed daily surveillance data for 367 children aged 0 to 12 years from 2 cohorts in a peri-urban shantytown in Lima, Peru, 1995 through 1998. We stratified diarrheal incidence by 6-month age categories, season, and El Niño, and modeled between-subject heterogeneity with random effects Poisson models.


Spring diarrheal incidence increased by 55% during El Niño compared with before El Niño. This increase was most acute among children older than 60 months, for whom the risk of a diarrheal episode during the El Niño spring was nearly 100% greater (relative risk = 1.96; 95% confidence interval = 1.24, 3.09).


El Niño–associated climate variability affects community rates of diarrhea, particularly during the cooler seasons and among older children. Public health officials should develop preventive strategies for future El Niño episodes to mitigate the increased risk of diarrheal disease in vulnerable communities.

The effect of weather on disease transmission is well recognized for many infectious diseases that exhibit seasonal patterns,1 including diarrhea,2,3 respiratory infections,4 malaria,5 and dengue.6 There is growing concern that severe weather changes resulting from El Niño episodes and global climate change directly affect human health.7 Diarrheal illnesses are among the highest disease burdens in children younger than 5 years of age worldwide8 and are predicted to increase with climate change. However, specific estimates for the magnitude of this increase in the community setting remain uncertain, in part because epidemiological data on the relationship between community rates of diarrhea and extreme weather variability are scarce.9 Although the relationship between specific weather variables and infectious disease has been examined extensively with retrospective, hospital-based data,1014 data from prospective population-based cohort studies are limited. Determining the effects of El Niño on rates of diarrhea with a cohort study would greatly improve our understanding of climate variability and diarrheal disease at the community level and inform predictions for other extreme weather episodes or future climate change scenarios.15

The El Niño southern oscillation (ENSO) is a main driver of global interannual weather variation. Occurring every 3 to 7 years, the ENSO phenomenon leads to extreme worldwide weather events, such as heavy flooding and drought.16 The ENSO provides health researchers with an opportunity to model effects of local climate anomalies on infectious disease dynamics,17 and it has been linked to changes in rates of cholera,1821 diarrhea,11,22,23 malaria,10 dengue,24 hantavirus,25 viral pneumonia,26 and Rift Valley fever.27

The 1997–1998 El Niño episode altered weather conditions around the world—particularly severely along the Peruvian coastline. This El Niño episode has been described as the strongest yet recorded.28 Previously, we found that the number of pediatric hospital admissions for diarrheal diseases in Lima, Peru, increased substantially during this episode, especially during the winter months.11 A separate study found similar results for adults.22 In this study, we sought to examine the effects of the 1997–1998 El Niño episode on rates of childhood diarrhea and several parasitic agents in a peri-urban Peruvian community with cohort studies conducted between June1995 and August 1998.


We used data from 2 separate but contemporaneous longitudinal cohorts comprising 367 children aged 0 to 12 years to study the epidemiology of diarrheal diseases before and during the 1997–1998 El Niño episode.

Study Setting

We conducted these studies in Pampas de San Juan, Peru, a well-described peri-urban shantytown2931 located 25 kilometers south of central Lima. The study took place between April 1995 and December 1998. More than 50% of study households had a private water connection at the time of the study, but most households also continued to use containers to store water obtained from delivery trucks and neighbors throughout this period.32 Roughly half of households had a home sewage connection.

Mean ambient temperature in Lima is typically 16°C to 19°C from May to November and 20°C to 26°C from December to April. Rainfall rarely exceeds 50 millimeters per year. Mean relative humidity is 84%.

Study Sample

We enrolled a cohort of 230 children of randomly selected pregnant women at birth, and surveyed them daily for up to 3 years.33 We excluded 5 children because of insufficient data before and during El Niño. Thus, we included 225 children from the cohort for this analysis. Over the same period, we conducted daily surveillance on a second cohort of 142 randomly selected children aged 1 month to 10 years and followed them for a minimum of 1 year and a maximum of 40 months.34 We stratified children in this second cohort by age to account for age differences in the risk of diarrhea. In this analysis, we left-censored the data at the start of the observation period on June 1, 1995 and censored all observations at the end of El Niño on August 31, 1998. We excluded children with fewer than 180 days of follow-up. We had data for most children both before and during El Niño, and all age groups were adequately represented in each period.

We collected daily records of diarrheal surveillance throughout the study period for both cohorts. During each daily visit, field workers asked the mother or caretaker about the number of liquid or semiliquid stools the child experienced during the previous 24-hour period and whether she or he thought the child was ill with diarrhea. At baseline, we collected socioeconomic data such as per capita household income, household size, sanitation facilities, and water sources from every household. We obtained meteorological data for the Jesús María weather station (15 km from Pampas) from SENAMHI (

Parasite Isolations

Parasitic infections known to exhibit distinct seasonality35 are prevalent in this community. We collected stool samples from children in both cohorts on a weekly basis and tested for several of the most common parasites in this population to evaluate if El Niño was associated with an increased or decreased rate of parasitic isolation.

We processed samples by ether concentration and examined them for Cryptosporidium spp. with light microscopy on modified acid-fast stained slides,36 for Giardia lamblia on direct wet mount,37 and for Cyclospora cayetanensis with epiflourescence and on direct wet mount.34


We defined a diarrheal episode as beginning on the day the child experienced 3 or more liquid or semiliquid stools during a 24-hour period and the mother or caretaker thought the child had diarrhea and ending when the child had fewer than 3 liquid or semiliquid stools for each of 2 consecutive days.

We defined the El Niño period as from April 1, 1997 to August 31, 1998, based on deviations from normal temperature observed in Lima.11,28 We confirmed this definition with SENAMHI’s meteorological data. We compared diarrhea rates during the El Niño episode to diarrhea rates during the period before El Niño (June 1, 1995 to March 31, 1997).

Biostatistical Methods

We analyzed rates of diarrhea and parasites in strata defined by season and age categories. We stratified rates of diarrhea during El Niño and pre–El Niño according to calendar quarters beginning on January 1. Age categories were 0 to 5 months, 6 to 11 months, 12 to 23 months, 24 to 59 months, and 60 months or older.

We modeled incidence of diarrhea with random effects Poisson regression models.38 We accounted for intersubject heterogeneity with a random intercept. To control for differential exposure time per child, we included the number of child-days at risk as an offset term. We fitted models with age (reference category: 0–5 months), season (reference period: January–March), and El Niño. We examined interactions between age, season, and El Niño through the successive inclusion of 2- and 3-way interaction terms. We used the Akaike information criterion to compare the final regression models. We chose the model with the lowest Akaike information criterion for final conclusions (data available as a supplement to the online version of this article at We used robust standard errors to adjust for within-subject correlation.

We first conducted separate analyses for each cohort. We then conducted analyses using the data for all children in a single regression. Because we obtained consistent results with both approaches, we present our final models on the basis of a single regression. In subset analyses of child participants with complete household data, we included gender, water source (reference category: home connection), sanitation (reference category: sewage connection), household size, and per capita household income in the final models.

We modeled diarrheal duration with a random effects Poisson model using the same modeling strategy. We found that the best model included no interactions between age, season, and El Niño. We modeled rates of infection with G. lamblia, Cryptosporidium spp., and C. cayetanensis with random effects Poisson models as a function of age, season, and El Niño and the interaction between season and El Niño. We collapsed the 2 youngest age categories into 1 category because of the small number of counts. We defined infection onset as when 1 or more weekly stool sample tested positive for the respective parasite and the end of an episode as when there were 3 or more consecutive negative weekly stool samples.36 In these models, we used the number of weekly stool samples per child as an offset.

We used Stata 10.0 (StataCorp LP, College Station, TX) and R version 2.8 ( for statistical analyses.


This study followed 367 children for 153 650 child-days before the El Niño period and 131 410 child-days during El Niño, for a total of 285 060 child-days (Table 1). Daily maximum, minimum, and mean ambient temperatures increased by as much as 5°C during El Niño (Table 2). Before El Niño, we observed 913 diarrhea episodes, and the unadjusted incidence rate of diarrhea was 2.2 episodes per child-year (95% confidence interval [CI] = 2.1, 2.4). During El Niño, we observed 859 diarrhea episodes, and the unadjusted incidence rate of diarrhea was 2.4 episodes per child-year (95% CI = 2.3, 2.6).

Sample Characteristics by Cohort: 1997–1998 El Niño Episode Effect on Diarrheal Incidence, Lima, Peru, 1995–1998
Average Daily Ambient Temperature by Season Before and During El Niño: 1997–1998 El Niño Episode Effect on Diarrheal Incidence, Lima, Peru, 1995–1998

Diarrheal Incidence and Duration

Pre–El Niño diarrheal incidence was highest among children aged 6 to 23 months (Table 3). Incidence increased during El Niño for all age categories, except for the youngest category (< 6 months). The percentage increase was greatest (31%) among the oldest children (≥ 60 months). Pre–El Niño diarrheal incidence was greatest during the summer (January–March) and fall (April–June) months. During El Niño, however, this seasonal pattern shifted so that the highest incidence occurred during El Niño spring months (October–December). Season-to-season variability in incidence decreased during El Niño: whereas diarrheal incidence decreased slightly during the El Niño summer and fall, it increased 55% from 1.73 episodes per child-year (95% CI = 1.50, 1.98) during the pre–El Niño spring to 2.69 (95% CI = 2.31, 3.13) during the El Niño spring. Gender, water source, household size, and per capita household income did not confound the relationship between El Niño and diarrheal incidence.

Incidence and Average Duration of Diarrheal Episodes Before and During the 1997–1998 El Niño, Stratified by Age, Category, and Season: Lima, Peru, 1995–1998

In the final model, the association between El Niño and diarrheal incidence was greatest among children 60 months and older, as diarrhea risk among these children nearly doubled during the El Niño spring months compared with before El Niño (relative risk [RR] = 1.96; 95% CI = 1.24, 3.09) and increased by 67% during the winter months (RR = 1.67; 95% CI = 1.03, 2.64; Table 4). Among children aged 6 to 11 months, the risk of a diarrheal episode increased by 70% during the El Niño spring months (RR = 1.70; 95% CI = 1.18, 2.43) and by 43% during the winter months (RR = 1.43; 95% CI = 1.00, 2.04).

RR and 95% CI of the Effect of the 1997–1998 El Niño Episode on Diarrheal Incidence by Age and Season: Lima, Peru, 1995–1998

Water source did not appear to confound the relationship between El Niño and rates of diarrhea. By contrast, we found an interaction between household sanitation and El Niño. Type of household sanitation modified the El Niño effect such that during the spring months, children aged 60 months and older in households with no sewage connection presented a statistically significant increase in risk during El Niño (RR = 2.23; 95% CI = 1.35, 3.67), whereas those with a sewage connection did not (RR = 1.59; 95% CI = 0.97, 2.62). Children aged 60 months and older in households with no sewage connection also experienced a significant increase during the winter months (RR = 1.91; 95% CI = 1.14, 3.21). During both winter and spring, children aged 6 to 11 months in households without a sewage connection experienced a statistically significant increase in diarrhea (winter: RR = 1.71; 95% CI = 1.16, 2.51; spring: RR = 1.99; 95% CI = 1.36, 2.91), whereas those with a sewage connection did not (winter: RR = 1.22; 95% CI = 0.82, 1.82; spring: RR = 1.42; 95% CI = 0.95, 2.14).

The average duration was longest among the youngest children (3 days) and decreased for each successive age category (to 1.8 days for children aged 60 months and older). Average duration was longest during the summer (2.4 days) and fall (2.7 days) months and shortest during the spring (2.2 days), but did not change appreciably during El Niño (RR = 1.03; 95% CI = 0.96, 1.12).

Parasite Isolations

The 367 children contributed 39 630 weekly stool samples. The overall incidence of Cryptosporidium spp. increased slightly from 0.35 infections per 100 child-weeks before El Niño (95% CI = 0.28, 0.45) to 0.39 infections per 100 child-weeks during El Niño (95% CI = 0.31, 0.50; Table 5), but this increase was not statistically significant. The incidence increased from 0.17 infections per 100 child-weeks (95% CI = 0.10, 0.28) to 0.36 infections per 100 child-weeks (95% CI = 0.26, 0.49) in the oldest age category. Infections were more common during the El Niño winter (0.24 per 100 child-weeks; 95% CI = 0.13, 0.40) and spring (0.52 per 100 child-weeks; 95% CI = 0.30, 0.84) than before El Niño (winter: 0.21 per 100 child-weeks; 95% CI = 0.10, 0.37; spring: 0.25 per 100 child-weeks; 95% CI = 0.14, 0.43). The effect during the spring months remained positive in the Poisson model after adjusting for age but was not statistically significant (RR = 2.05; 95% CI = 0.92, 4.54).

Incidence Rates of Diarrheal Infections Before and During the 1997–1998 El Niño Episode: Lima, Peru, 1995–1998

The incidence of C. cayetanensis increased from 0.35 infections per 100 child-weeks (95% CI = 0.27, 0.44) before El Niño to 0.46 infections per 100 child-weeks (95% CI = 0.37, 0.57) during El Niño. Infections were more common among children older than 60 months in both periods (pre–El Niño: 0.55 infections per 100 child-weeks; 95% CI = 0.41, 0.73; El Niño: 0.66 infections per 100 child-weeks; 95% CI = 0.52, 0.83). There was an increase in Cyclospora infections during the El Niño winter (0.33 infections per 100 child-weeks; 95% CI = 0.20, 0.52) and spring (0.40 infections per 100 child-weeks; 95% CI = 0.21, 0.69) compared with pre–El Niño winter (0.09 infections per 100 child-weeks; 95% CI = 0.03, 0.22) and spring (0.13 infections per 100 child-weeks; 95% CI = 0.05, 0.26), respectively. Although crude incidence rates did not achieve statistical significance, the increase in Cyclospora incidence was significant in the Poisson model after adjusting for age and season (winter: RR = 2.87; 95% CI = 1.07, 7.66; spring: RR = 2.46; 95% CI = 0.94, 6.43).

The incidence of G. lamblia decreased from 6.67 infections per 100 child-weeks (95% CI = 6.30, 7.07) before El Niño to 5.19 infections per 100 child-weeks (95% CI = 4.85, 5.56) during El Niño. This decrease was consistent for all age categories and most marked during winter and spring, when incidence fell from 7.56 (95% CI = 6.78, 8.40) to 4.69 (95% CI = 4.08, 5.36) infections per 100 child-weeks and from 7.60 (95% CI = 6.83, 8.44) to 4.92 (95% CI = 4.13, 5.82) infections per 100 child-weeks, respectively. These decreases were significant in the Poisson model (winter: RR = 0.55; 95% CI = 0.48, 0.64; spring: RR = 0.56; 95% CI = 0.47, 0.65).


We have presented an analysis of the association between the 1997–1998 El Niño episode and rates of diarrhea in a community-based cohort of children. Our models showed important interactions between El Niño, season, and age. The association between El Niño and rates of diarrhea was greatest during the spring trimester, October through December; less pronounced during the winter trimester, July through September; and negative during the fall trimester, April though June. This seasonal effect of El Niño was greatest among children aged 60 months and older. Among these children, the rate of diarrhea in the spring during El Niño was almost double the rate during the spring before El Niño. Finally, El Niño was associated with higher rates of diarrhea for children in households without a sewage connection than for those in households with a sewage connection. These results are consistent with findings for the 1997–1998 El Niño episode derived from diarrheal admissions to oral rehydration units.8 In this community-based study, we found that El Niño increased diarrheal incidence during the normally cooler winter and spring, when rates nearly doubled for older children, but did not influence illness duration.

Common causes of infectious diarrhea follow seasonal patterns.35,39, In general, higher temperatures are associated with increased reproductive rates of microorganisms, and therefore rates of diarrheal disease are higher in warmer seasons.41 This is the case for most bacterial causes of diarrhea, such as bacillary dysentery.35, However, this relationship does not always hold. For example, some common viral causes of diarrhea, such as norovirus and rotavirus, are often more prevalent during cooler seasons.43 Furthermore, some studies have suggested that in some cases high tropical temperatures may inhibit oocyst survival, reducing parasite viability.44 As a result, the relationship between temperature and diarrheal disease may be nonlinear.12,45 In this study, we found that higher mean temperatures in the cooler seasons during El Niño were associated with an increased risk of diarrhea by as much as 96%, whereas in the warmer seasons risk was unchanged or slightly lower.

Furthermore, we found that adjusted rates of C. cayetanensis in weekly stool samples increased during El Niño, most markedly so in the cooler seasons when these are normally rare infections. This increase was likely because of increased sporulation with higher temperatures.46 By contrast, G. lamblia in weekly stool samples decreased during El Niño. This decrease likely did not greatly influence diarrhea rates, as earlier work in this community found no pathogenic effect for Giardia,37 but it may reflect the fact that Giardia behaves commensally in this population. These results indicate that the effect of the El Niño conditions of higher mean temperature and lower humidity in Lima on diarrhea rates varies by both season and pathogen distribution.

Our finding of a greater positive association between El Niño and diarrhea risk among older children suggests behavioral factors may play a role in increasing the risk of infection by water- and food-borne pathogens during an El Niño episode. Older children may be more likely to be outside the home and therefore exposed to temperature-sensitive pathogens in food and water from markets and small stores. This is consistent with previous work in this community that has demonstrated the viability and persistence of Cryptosporidium parvum and C. cayetanensis in market vegetables during normal summer months.47 Additionally, lacking a home sewage connection increases the vulnerability of children to El Niño–related temperature changes, as these children are more likely to use a latrine outside the home.

Most studies on the health effects associated with El Niño episodes have used retrospective, hospital-based data. In contrast, there are few studies examining the association between climate variability and diarrhea rates with a population-based cohort study.48 We believe that our longitudinal study during one of the strongest El Niño episodes in 1 community affords a unique contribution to understanding the effects of extreme weather variability owing to El Niño in the community-based setting. Namely, our finding that El Niño may increase susceptibility to environmental pathogens, but does not influence illness duration, is important for improving diarrheal disease burden estimates with climate change.

Longitudinal population-based data provide us with a more complete view of the epidemiology of diarrhea than do hospital-based data for several reasons. First, hospital patient data may represent a distinct subpopulation and vary in quality with patient load. Hospital patient data are subject to self-selection bias, as differential health care access and health-seeking behavior affect rates of consultation and admission. An increase in health-seeking behavior in Peru owing to abnormal weather conditions and publicity surrounding the El Niño episode as well as concerns for cholera may have led to increased numbers of visits to hospitals. Second, hospital cases often represent more severe, acute disease; individuals with mild symptoms may not visit a clinic. It is possible that this El Niño episode led primarily to an increase in severe disease. Population-based data allow us to capture more subtle changes in disease rates. Finally, population-based data allow us to model specific individuals over time, which may help identify risk factors associated with increases of diarrhea during El Niño episodes.

However, demonstrating an effect in a community-based study proves more difficult because longitudinal cohorts with intensive surveillance are usually small (< 250 participants) because of the costliness of daily visits, and disease symptoms are likely milder. Therefore, demonstrating an effect of El Niño conditions on diarrhea rates in a population-based cohort greatly strengthens the conclusions from hospital-based studies.


Limited data before El Niño across age categories made it difficult to detect a stronger El Niño effect. Data were available only for a relatively short pre–El Niño period (approximately 22 months), and we recruited many children midway through this period. Hence, inferences for the baseline risk during the period before El Niño were imprecise. Furthermore, as rates of diarrheal disease are in general greater among younger children (< 2 years) and during warmer seasons, the assessment of an El Niño effect required that we account for seasonal patterns and the changing age distribution of children over time.

The heterogeneity in our study population and reduced sizes of strata defined by age, season, and El Niño may have weakened the significance of an effect of El Niño. We were not able to assess the effect of El Niño on the incidence of bacterial or viral pathogens; however, we examined the effect of El Niño on parasitic infections using more than 30 000 weekly stool samples. We were also not able to properly examine the effect of El Niño on dehydration status or hospitalizations given our small sample size; however, our previous work identified that El Niño had a profound effect on the number of admissions11 for dehydration to an oral rehydration unit in Lima. Finally, we were able to model only a single El Niño episode, and we lacked substantial data following the El Niño period, which would have allowed us to rule out secular trends.


Our data show that the 1997–1998 El Niño episode was associated with increased diarrhea risk in a shantytown in Lima, Peru during the normally lower incidence winter and spring seasons but was not associated with increased illness duration. Our results highlight the importance of considering seasonality, pathogen distribution, and sanitation infrastructure when evaluating the effects of climate change on diarrheal disease. In addition to preparing for the more catastrophic weather events associated with El Niño, public health attention should focus on strategies to anticipate and mitigate the increased risk of diarrheal disease during specific seasons in these vulnerable communities.

El Niño episodes can be predicted with several months of advance warning. Hence, health officials can increase educational messaging in anticipation of a strong episode and advise communities on water treatment and sanitation efforts to mitigate the effects on diarrheal disease.


This study was funded in part by a joint National Science Foundation, Environmental Protection Agency, National Aeronautics and Space Administration, Electric Power Research Institute, and National Oceanic and Atmospheric Administration grant on climate variability and human health; by the Applied Research on Child Health project grants program; and by an International Centers for Tropical Disease Research grant from the National Institutes of Allergy and Infectious Diseases awarded to the Johns Hopkins Bloomberg School of Public Health (grant U01-A135894). A. Bennett was a Fogarty International Clinical Research Scholar (grant R24-TW007988) during this work. A. G. Lescano was sponsored by a grant awarded to NAMRU-6 by the Fogarty International Center, National Institutes of Health (grant D43TW007393). W. Checkley was further supported by a Clinician Scientist Award from the Johns Hopkins University and a K99/R00 Pathway to Independence Award (award K99HL096955) from the National Heart, Lung, and Blood Institute, National Institutes of Health.



A. Bennett and L. D. Epstein were responsible for data analysis. R. H. Gilman and W. Checkley originated the study design. W. Checkley had ultimate oversight over study design and administration and was responsible for data analysis. He had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis. All authors contributed equally to the study design, data interpretation, and writing of the article.

Human Participant Protection

The internal review boards of the Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, and Asociación Benéfica PRISMA, Lima, Peru, approved the study.


1. Fisman DN. Seasonality of infectious diseases. Annu Rev Public Health. 2007;28:127–143. [PubMed]
2. Guerrant RL, Kirchhoff LV, Shields DS, et al. Prospective study of diarrheal illnesses in northeastern Brazil: patterns of disease, nutritional impact, etiologies, and risk factors. J Infect Dis. 1983;148(6):986–997. [PubMed]
3. Singh RB, Hales S, de Wet N, Raj R, Hearnden M, Weinstein P. The influence of climate variation and change on diarrheal disease in the Pacific Islands. Environ Health Perspect. 2001;109(2):155–159. [PMC free article] [PubMed]
4. Moura FE, Nunes IF, Silva GB, Jr, Siqueira MM. Respiratory syncytial virus infections in northeastern Brazil: seasonal trends and general aspects. Am J Trop Med Hyg. 2006;74(1):165–167. [PubMed]
5. Mabaso ML, Craig M, Ross A, Smith T. Environmental predictors of the seasonality of malaria transmission in Africa: the challenge. Am J Trop Med Hyg. 2007;76(1):33–38. [PubMed]
6. Johansson MA, Dominici F, Glass GE. Local and global effects of climate on dengue transmission in Puerto Rico. PLoS Negl Trop Dis. 2009;3(2):e382. [PMC free article] [PubMed]
7. Patz JA, Campbell-Lendrum D, Holloway T, Foley JA. Impact of regional climate change on human health. Nature. 2005;438(7066):310–317. [PubMed]
8. Guerrant RL, Kosek M, Lima AA, Lorntz B, Guyatt HL. Updating the DALYs for diarrhoeal disease. Trends Parasitol. 2002;18(5):191–193. [PubMed]
9. Kolstad EW, Johansson KA. Uncertainties associated with quantifying climate change impacts on human health: a case study for diarrhea. Environ Health Perspect. 2011;119(3):299–305. [PMC free article] [PubMed]
10. Bouma MJ, Dye C. Cycles of malaria associated with El Niño in Venezuela. JAMA. 1997;278(21):1772–1774. [PubMed]
11. Checkley W, Epstein LD, Gilman RH, et al. Effect of El Niño and ambient temperature on hospital admissions for diarrhoeal diseases in Peruvian children. Lancet. 2000;355(9202):442–450. [PubMed]
12. Hashizume M, Armstrong B, Wagatsuma Y, Faruque AS, Hayashi T, Sack DA. Rotavirus infections and climate variability in Dhaka, Bangladesh: a time-series analysis. Epidemiol Infect. 2008;136(9):1281–1289. [PubMed]
13. Luz PM, Mendes BV, Codeço CT, Struchiner CJ, Galvani AP. Time series analysis of dengue incidence in Rio de Janeiro, Brazil. Am J Trop Med Hyg. 2008;79(6):933–939. [PubMed]
14. Hashizume M, Armstrong B, Hajat S, et al. Association between climate variability and hospital visits for non-cholera diarrhoea in Bangladesh: effects and vulnerable groups. Int J Epidemiol. 2007;36(5):1030–1037. [PubMed]
15. Campbell-Lendrum D, Woodruff R. Comparative risk assessment of the burden of disease from climate change. Environ Health Perspect. 2006;114(12):1935–1941. [PMC free article] [PubMed]
16. Glantz M. Currents of Change: Impacts of El Niño and La Niña on Climate and Society. Cambridge: Cambridge University Press; 2001.
17. Kovats RS, Bouma MJ, Shakoor H, Worrall E, Haines A. El Niño and health. Lancet. 2003;362(9394):1481–1489. [PubMed]
18. Rodo X, Pascual M, Fuchs G, Faruque AS. ENSO and cholera: a nonstationary link related to climate change? Proc Natl Acad Sci USA. 2002;99(20):12901–12906. [PubMed]
19. Seas C, Miranda J, Gil AI, et al. New insights on the emergence of cholera in Latin America during 1991: the Peruvian experience. Am J Trop Med Hyg. 2000;62(4):513–517. [PubMed]
20. Speelmon EC, Checkley W, Gilman RH, Patz J, Calderon M, Manga S. Cholera incidence and El Niño-related higher ambient temperature. JAMA. 2000;283(23):3072–3074. [PubMed]
21. Martinez-Urtaza J, Huapaya B, Gavilan RG, et al. Emergence of Asiatic Vibrio diseases in South America in phase with El Niño. Epidemiology. 2008;19(6):829–837. [PubMed]
22. Lama JR, Seas CR, León-Barúa R, Gotuzzo E, Sack RB. Environmental temperature, cholera, and acute diarrhoea in adults in Lima, Peru. J Health Popul Nutr. 2004;22(4):399–403. [PubMed]
23. Salazar-Lindo E, Pinell-Salles P, Maruy A, Chea-Woo E. El Niño and diarrhoea and dehydration in Lima, Peru. Lancet. 1997;350(9091):1597–1598. [PubMed]
24. Cazelles B, Chavez M, McMichael AJ, Hales S. Nonstationary influence of El Niño on the synchronous dengue epidemics in Thailand. PLoS Med. 2005;2(4):e106. [PMC free article] [PubMed]
25. Hjelle B, Glass GE. Outbreak of hantavirus infection in the Four Corners region of the United States in the wake of the 1997–1998 El Niño-southern oscillation. J Infect Dis. 2000;181(5):1569–1573. [PubMed]
26. Ebi KL, Exuzides KA, Lau E, Kelsh M, Barnston A. Association of normal weather periods and El Niño events with hospitalization for viral pneumonia in females: California, 1983–1998. Am J Public Health. 2001;91(8):1200–1208. [PubMed]
27. Anyamba A, Chretien JP, Small J, et al. Prediction of a Rift Valley fever outbreak. Proc Natl Acad Sci USA. 2009;106(3):955–959. [PubMed]
28. Bell GD, Halpert MS, Kousky VE, et al. Climate assessment for 1998. Bull Am Meteorol Soc. 1999;80(5):1040.
29. Fernández-Concha D, Gilman RH, Gilman JB. A home nutritional rehabilitation programme in a Peruvian peri-urban shanty town (Pueblo Joven) Trans R Soc Trop Med Hyg. 1991;85(6):809–813. [PubMed]
30. Checkley W, Epstein LD, Gilman RH, Black RE, Cabrera L, Sterling CR. Effects of Cryptosporidium parvum infection in Peruvian children: growth faltering and subsequent catch-up growth. Am J Epidemiol. 1998;148(5):497–506. [PubMed]
31. Berkman DS, Lescano AG, Gilman RH, Lopez SL, Black MM. Effects of stunting, diarrhoeal disease, and parasitic infection during infancy on cognition in late childhood: a follow-up study. Lancet. 2002;359(9306):564–571. [PubMed]
32. Checkley W, Gilman RH, Black RE, et al. Effect of water and sanitation on childhood health in a poor Peruvian peri-urban community. Lancet. 2004;363(9403):112–118. [PubMed]
33. Checkley W, Gilman RH, Black RE, et al. Effects of nutritional status on diarrhea in Peruvian children. J Pediatr. 2002;140(2):210–218. [PubMed]
34. Bern C, Ortega Y, Checkley W, et al. Epidemiologic differences between cyclosporiasis and cryptosporidiosis in Peruvian children. Emerg Infect Dis. 2002;8(6):581–585. [PMC free article] [PubMed]
35. Naumova EN, Jagai JS, Matyas B, DeMaria A, Jr, MacNeill IB, Griffiths JK. Seasonality in six enterically transmitted diseases and ambient temperature. Epidemiol Infect. 2007;135(2):281–292. [PubMed]
36. Cama VA, Bern C, Roberts J, et al. Cryptosporidium species and subtypes and clinical manifestations in children, Peru. Emerg Infect Dis. 2008;14(10):1567–1574. [PMC free article] [PubMed]
37. Hollm-Delgado MG, Gilman RH, Bern C, et al. Lack of an adverse effect of Giardia intestinalis infection on the health of Peruvian children. Am J Epidemiol. 2008;168(6):647–655. [PMC free article] [PubMed]
38. McCullough P, Nelder J. Generalized Linear Models. 2nd ed. London; Chapman and Hall; 1989.
39. Kovats RS, Edwards SJ, Charron D, et al. Climate variability and Campylobacter infection: an international study. Int J Biometeorol. 2005;49(4):207–214. [PubMed]
40. Jagai JS, Castronovo DA, Monchak J, Naumova EN. Seasonality of cryptosporidiosis: a meta-analysis approach. Environ Res. 2009;109(4):465–478. [PMC free article] [PubMed]
41. Black RE, Lanata CF. Epidemiology of diarrheal diseases in developing countries. In: Blaser MJ, Smith PD, Greenberg HB, Guerrant RL, Ravdin JI, editors. Infections of the Gastrointestinal Tract. New York: Raven Press; 1995. pp. 17–35.
42. Zhang Y, Bi P, Hiller JE, Sun Y, Ryan P. Climate variations and bacillary dysentery in northern and southern cities of China. J Infect. 2007;55(2):194–200. [PubMed]
43. D’Souza RM, Hall G, Becker NG. Climatic factors associated with hospitalizations for rotavirus diarrhoea in children under 5 years of age. Epidemiol Infect. 2008;136(1):56–64. [PubMed]
44. Eberhard ML, Nace EK, Freeman AR, Streit TG, da Silva AJ, Lammie PJ. Cyclospora cayetanensis infections in Haiti: a common occurrence in the absence of watery diarrhea. Am J Trop Med Hyg. 1999;60(4):584–586. [PubMed]
45. Onozuka D, Hashizume M. Weather variability and paediatric infectious gastroenteritis. Epidemiol Infect. 2011;139(9):1369–1378. [PubMed]
46. Ortega YR, Sterling CR, Gilman RH. Cyclospora cayetanensis. Adv Parasitol. 1998;40:399–418. [PubMed]
47. Ortega YR, Roxas CR, Gilman RH, et al. Isolation of Cryptosporidium parvum and Cyclospora cayetanensis from vegetables collected in markets of an endemic region in Peru. Am J Trop Med Hyg. 1997;57(6):683–686. [PubMed]
48. Newman RD, Sears CL, Moore SR, et al. Longitudinal study of Cryptosporidium infection in children in northeastern Brazil. J Infect Dis. 1999;180(1):167–175. [PubMed]