The Variability of Childhood Diarrhea in Karachi, Pakistan, 2002–2006

Luby, Stephen P.; Agboatwalla, Mubina; Hoekstra, Robert M.

doi:10.4269/ajtmh.2011.10-0364

Cited by 19 publications

(16 citation statements)

References 24 publications

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“…Most demographic variables commonly assessed at recruitment, such as date of birth, gender, family size or socio-economic status, do not change rapidly (if at all) and may later be used to adjust for imbalances. In contrast, diarrhoea prevalence is highly variable over time 60 . If an individual has diarrhoea at baseline, it indicates that they may be more prone to diarrhoea during the follow-up period, but this depends on the within-person clustering of disease in a given setting.…”

Section: Literature Search Methods and Data Setsmentioning

confidence: 99%

“…As Figure 1 illustrates, baseline incidence bears no relation to incidence during the year-long intervention period. Several factors may have contributed to this, such as the long gap between baseline measurement and the actual trial and, in particular, the high spatial and temporal variability of diarrhoea often observed in the field 60 . This contrasts with strong associations between baseline village HIV prevalence and subsequent incidence, 62 or between baseline height-for-age Z -scores and subsequent height measurements 63 …”

Section: Literature Search Methods and Data Setsmentioning

confidence: 99%

See 1 more Smart Citation

Epidemiological methods in diarrhoea studies—an update

Schmidt

Arnold

Boisson

et al. 2011

International Journal of Epidemiology

112

118

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Background Diarrhoea remains a leading cause of morbidity and mortality but is difficult to measure in epidemiological studies. Challenges include the diagnosis based on self-reported symptoms, the logistical burden of intensive surveillance and the variability of diarrhoea in space, time and person.Methods We review current practices in sampling procedures to measure diarrhoea, and provide guidance for diarrhoea measurement across a range of study goals. Using 14 available data sets, we estimated typical design effects for clustering at household and village/neighbourhood level, and measured the impact of adjusting for baseline variables on the precision of intervention effect estimates.Results Incidence is the preferred outcome measure in aetiological studies, health services research and vaccine trials. Repeated prevalence measurements (longitudinal prevalence) are appropriate in high-mortality settings where malnutrition is common, although many repeat measures are rarely useful. Period prevalence is an inadequate outcome if an intervention affects illness duration. Adjusting point estimates for age or diarrhoea at baseline in randomized trials has little effect on the precision of estimates. Design effects in trials randomized at household level are usually <2 (range 1.0–3.2). Design effects for larger clusters (e.g. villages or neighbourhoods) vary greatly among different settings and study designs (range 0.1–25.8).Conclusions Using appropriate sampling strategies and outcome measures can improve the efficiency, validity and comparability of diarrhoea studies. Allocating large clusters in cluster randomized trials is compromized by unpredictable design effects and should be carried out only if the research question requires it.

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Section: Literature Search Methods and Data Setsmentioning

confidence: 99%

Section: Literature Search Methods and Data Setsmentioning

confidence: 99%

Epidemiological methods in diarrhoea studies—an update

Schmidt

Arnold

Boisson

et al. 2011

International Journal of Epidemiology

112

118

View full text Add to dashboard Cite

show abstract

“…The limitation of this study is that we used a 14-day recall period, which might have increased the subjectivity of reporting. Another limitation of the study is one-time observation after the intervention, which hindered us from exploring the seasonal variation of the improved water effect, even though diarrheal prevalence highly varies between dry and rainy seasons [ 36 ]. Considering ethical issues, however, we had to reduce the delay time of providing the improved water supply to the control communities as short a period as possible.…”

Section: Discussionmentioning

confidence: 99%

The Effect of Improved Water Supply on Diarrhea Prevalence of Children under Five in the Volta Region of Ghana: A Cluster-Randomized Controlled Trial

Cha

Kang²,

Tuffuor³

et al. 2015

IJERPH

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Although a number of studies have been conducted to explore the effect of water quality improvement, the majority of them have focused mainly on point-of-use water treatment, and the studies investigating the effect of improved water supply have been based on observational or inadequately randomized trials. We report the results of a matched cluster randomized trial investigating the effect of improved water supply on diarrheal prevalence of children under five living in rural areas of the Volta Region in Ghana. We compared the diarrheal prevalence of 305 children in 10 communities of intervention with 302 children in 10 matched communities with no intervention (October 2012 to February 2014). A modified Poisson regression was used to estimate the prevalence ratio. An intention-to-treat analysis was undertaken. The crude prevalence ratio of diarrhea in the intervention compared with the control communities was 0.85 (95% CI 0.74–0.97) for Krachi West, 0.96 (0.87–1.05) for Krachi East, and 0.91 (0.83–0.98) for both districts. Sanitation was adjusted for in the model to remove the bias due to residual imbalance since it was not balanced even after randomization. The adjusted prevalence ratio was 0.82 (95% CI 0.71–0.96) for Krachi West, 0.95 (0.86–1.04) for Krachi East, and 0.89 (0.82–0.97) for both districts. This study provides a basis for a better approach to water quality interventions.

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“…In diarrhoea CRTs, the design effect not only depends on the temporal and spatial variation of diarrhoea between clusters (which can be considerable [16]) but also on the number of follow-up surveys and the within-person correlation of diarrhoea, making the design effect difficult to predict [17]. We chose the proportion of days with diarrhoea (longitudinal prevalence) as the outcome for the sample size calculation [17].…”

Section: Methodsmentioning

confidence: 99%

The effect of improved rural sanitation on diarrhoea and helminth infection: design of a cluster-randomized trial in Orissa, India

Clasen

Boisson

Routray

et al. 2012

Emerg Themes Epidemiol

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BackgroundInfectious diseases associated with poor sanitation such as diarrhoea, intestinal worms, trachoma and lymphatic filariasis continue to cause a large disease burden in low income settings and contribute substantially to child mortality and morbidity. Obtaining health impact data for rural sanitation campaigns poses a number of methodological challenges. Here we describe the design of a village-level cluster-randomised trial in the state of Orissa, India to evaluate the impact of an ongoing rural sanitation campaign conducted under the umbrella of India’s Total Sanitation Campaign (TSC).We randomised 50 villages to the intervention and 50 villages to control. In the intervention villages the implementing non-governmental organisations conducted community mobilisation and latrine construction with subsidies given to poor families. Control villages receive no intervention. Outcome measures include (1) diarrhoea in children under 5 and in all ages, (2) soil-transmitted helminth infections, (3) anthropometric measures, (4) water quality, (5) number of insect vectors (flies, mosquitoes), (6) exposure to faecal pathogens in the environment. In addition we are conducting process documentation (latrine construction and use, intervention reach), cost and cost-effectiveness analyses, spatial analyses and qualitative research on gender and water use for sanitation.ResultsRandomisation resulted in an acceptable balance between trial arms. The sample size requirements appear to be met for the main study outcomes. Delays in intervention roll-out caused logistical problems especially for the planning of health outcome follow-up surveys. Latrine coverage at the end of the construction period (55%) remained below the target of 70%, a result that may, however, be in line with many other TSC intervention areas in India.ConclusionWe discuss a number of methodological problems encountered thus far in this study that may be typical for sanitation trials. Nevertheless, it is expected that the trial procedures will allow measuring the effectiveness of a typical rural sanitation campaign, with sufficient accuracy and validity.

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The Variability of Childhood Diarrhea in Karachi, Pakistan, 2002–2006

Cited by 19 publications

References 24 publications

Epidemiological methods in diarrhoea studies—an update

Epidemiological methods in diarrhoea studies—an update

The Effect of Improved Water Supply on Diarrhea Prevalence of Children under Five in the Volta Region of Ghana: A Cluster-Randomized Controlled Trial

The effect of improved rural sanitation on diarrhoea and helminth infection: design of a cluster-randomized trial in Orissa, India

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