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A novel approach for measuring the burden of uncomplicated Plasmodium falciparum malaria: application to data from Zambia.

Crowell V, Yukich JO, Briët OJ, Ross A, Smith TA - PLoS ONE (2013)

Bottom Line: The use of burden estimates that do not consider effects of treatment, leads to under-estimation of the impact of improvements in case management.Official estimates of burden very likely massively underestimate the impact of the roll-out of ACT as first-line therapy across Africa.The estimates of recall bias, and of the numbers of days with illness contributing to single illness recalls, could be applied more generally.

View Article: PubMed Central - PubMed

Affiliation: Department of Epidemiology and Public Health, Swiss Tropical and Public Health Institute, Basel, Switzerland.

ABSTRACT
Measurement of malaria burden is fraught with complexity, due to the natural history of the disease, delays in seeking treatment or failure of case management. Attempts to establish an appropriate case definition for a malaria episode has often resulted in ambiguities and challenges because of poor information about treatment seeking, patterns of infection, recurrence of fever and asymptomatic infection. While the primary reason for treating malaria is to reduce disease burden, the effects of treatment are generally ignored in estimates of the burden of malaria morbidity, which are usually presented in terms of numbers of clinical cases or episodes, with the main data sources being reports from health facilities and parasite prevalence surveys. The use of burden estimates that do not consider effects of treatment, leads to under-estimation of the impact of improvements in case management. Official estimates of burden very likely massively underestimate the impact of the roll-out of ACT as first-line therapy across Africa. This paper proposes a novel approach for estimating burden of disease based on the point prevalence of malaria attributable disease, or equivalently, the days with malaria fever in unit time. The technique makes use of data available from standard community surveys, analyses of fever patterns in malaria therapy patients, and data on recall bias. Application of this approach to data from Zambia for 2009-2010 gave an estimate of 2.6 (95% credible interval: 1.5-3.7) malaria attributable fever days per child-year. The estimates of recall bias, and of the numbers of days with illness contributing to single illness recalls, could be applied more generally. To obtain valid estimates of the overall malaria burden using these methods, there remains a need for surveys to include the whole range of ages of hosts in the population and for data on seasonality patterns in confirmed case series.

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Related in: MedlinePlus

Effect of bout duration on period prevalence in the malaria therapy data.a: distribution of durations of uninterrupted bouts of fever in the malaria therapy data; b: period prevalence of malaria fever in the malaria therapy patients, as a function of the duration of the period.
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pone-0057297-g003: Effect of bout duration on period prevalence in the malaria therapy data.a: distribution of durations of uninterrupted bouts of fever in the malaria therapy data; b: period prevalence of malaria fever in the malaria therapy patients, as a function of the duration of the period.

Mentions: Naively, the probability that a survey respondent reports fever, conditional on fever having occurred during a two week reference period might be thought to be , however, fever bouts extend over multiple days (Figure 3a), and there may be multiple bouts during a single reference period (Figure 1), so the overall recall bias depends on the natural history of the disease. An estimate of the overall recall probability for a two week period, allowing for these effects, , was obtained by applying the estimates of obtained from children in the Asembo study, to simulated interviews of malaria therapy patients, on the assumption that the number and pattern of days with fever during an arbitrary fourteen-day interval was similar in the field to those recorded in malaria therapy. The full recorded follow-up periods for malaria therapy patients were divided into fourteen-day intervals during which there was daily monitoring, leading to a total of 3715 fourteen-day intervals, during 755 of which there were one or more days with fever. Data were discarded for days that could not be included in these intervals because of gaps in, or termination of, the patients’ follow-up periods. For the analysis of recall in the absence of treatment, each day (j = 1, 2, …, 14) in each of these intervals was evaluated as though the patient had been interviewed at j = 14. Each day of fever was assumed recalled with probability (obtained from children in the Asembo study) so that the probability that any fever was recalled in the simulation was where if there was fever on day j and if there was no fever on day j.


A novel approach for measuring the burden of uncomplicated Plasmodium falciparum malaria: application to data from Zambia.

Crowell V, Yukich JO, Briët OJ, Ross A, Smith TA - PLoS ONE (2013)

Effect of bout duration on period prevalence in the malaria therapy data.a: distribution of durations of uninterrupted bouts of fever in the malaria therapy data; b: period prevalence of malaria fever in the malaria therapy patients, as a function of the duration of the period.
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC3585385&req=5

pone-0057297-g003: Effect of bout duration on period prevalence in the malaria therapy data.a: distribution of durations of uninterrupted bouts of fever in the malaria therapy data; b: period prevalence of malaria fever in the malaria therapy patients, as a function of the duration of the period.
Mentions: Naively, the probability that a survey respondent reports fever, conditional on fever having occurred during a two week reference period might be thought to be , however, fever bouts extend over multiple days (Figure 3a), and there may be multiple bouts during a single reference period (Figure 1), so the overall recall bias depends on the natural history of the disease. An estimate of the overall recall probability for a two week period, allowing for these effects, , was obtained by applying the estimates of obtained from children in the Asembo study, to simulated interviews of malaria therapy patients, on the assumption that the number and pattern of days with fever during an arbitrary fourteen-day interval was similar in the field to those recorded in malaria therapy. The full recorded follow-up periods for malaria therapy patients were divided into fourteen-day intervals during which there was daily monitoring, leading to a total of 3715 fourteen-day intervals, during 755 of which there were one or more days with fever. Data were discarded for days that could not be included in these intervals because of gaps in, or termination of, the patients’ follow-up periods. For the analysis of recall in the absence of treatment, each day (j = 1, 2, …, 14) in each of these intervals was evaluated as though the patient had been interviewed at j = 14. Each day of fever was assumed recalled with probability (obtained from children in the Asembo study) so that the probability that any fever was recalled in the simulation was where if there was fever on day j and if there was no fever on day j.

Bottom Line: The use of burden estimates that do not consider effects of treatment, leads to under-estimation of the impact of improvements in case management.Official estimates of burden very likely massively underestimate the impact of the roll-out of ACT as first-line therapy across Africa.The estimates of recall bias, and of the numbers of days with illness contributing to single illness recalls, could be applied more generally.

View Article: PubMed Central - PubMed

Affiliation: Department of Epidemiology and Public Health, Swiss Tropical and Public Health Institute, Basel, Switzerland.

ABSTRACT
Measurement of malaria burden is fraught with complexity, due to the natural history of the disease, delays in seeking treatment or failure of case management. Attempts to establish an appropriate case definition for a malaria episode has often resulted in ambiguities and challenges because of poor information about treatment seeking, patterns of infection, recurrence of fever and asymptomatic infection. While the primary reason for treating malaria is to reduce disease burden, the effects of treatment are generally ignored in estimates of the burden of malaria morbidity, which are usually presented in terms of numbers of clinical cases or episodes, with the main data sources being reports from health facilities and parasite prevalence surveys. The use of burden estimates that do not consider effects of treatment, leads to under-estimation of the impact of improvements in case management. Official estimates of burden very likely massively underestimate the impact of the roll-out of ACT as first-line therapy across Africa. This paper proposes a novel approach for estimating burden of disease based on the point prevalence of malaria attributable disease, or equivalently, the days with malaria fever in unit time. The technique makes use of data available from standard community surveys, analyses of fever patterns in malaria therapy patients, and data on recall bias. Application of this approach to data from Zambia for 2009-2010 gave an estimate of 2.6 (95% credible interval: 1.5-3.7) malaria attributable fever days per child-year. The estimates of recall bias, and of the numbers of days with illness contributing to single illness recalls, could be applied more generally. To obtain valid estimates of the overall malaria burden using these methods, there remains a need for surveys to include the whole range of ages of hosts in the population and for data on seasonality patterns in confirmed case series.

Show MeSH
Related in: MedlinePlus