Dataset Information

Malaria Incidence Rates from Time Series of 2-Wave Panel Surveys.

ABSTRACT: Methodology to estimate malaria incidence rates from a commonly occurring form of interval-censored longitudinal parasitological data-specifically, 2-wave panel data-was first proposed 40 years ago based on the theory of continuous-time homogeneous Markov Chains. Assumptions of the methodology were suitable for settings with high malaria transmission in the absence of control measures, but are violated in areas experiencing fast decline or that have achieved very low transmission. No further developments that can accommodate such violations have been put forth since then. We extend previous work and propose a new methodology to estimate malaria incidence rates from 2-wave panel data, utilizing the class of 2-component mixtures of continuous-time Markov chains, representing two sub-populations with distinct behavior/attitude towards malaria prevention and treatment. Model identification, or even partial identification, requires context-specific a priori constraints on parameters. The method can be applied to scenarios of any transmission intensity. We provide an application utilizing data from Dar es Salaam, an area that experienced steady decline in malaria over almost five years after a larviciding intervention. We conducted sensitivity analysis to account for possible sampling variation in input data and model assumptions/parameters, and we considered differences in estimates due to submicroscopic infections. Results showed that, assuming defensible a priori constraints on model parameters, most of the uncertainty in the estimated incidence rates was due to sampling variation, not to partial identifiability of the mixture model for the case at hand. Differences between microscopy- and PCR-based rates depend on the transmission intensity. Leveraging on a method to estimate incidence rates from 2-wave panel data under any transmission intensity, and from the increasing availability of such data, there is an opportunity to foster further methodological developments, particularly focused on partial identifiability and the diversity of a priori parameter constraints associated with different human-ecosystem interfaces. As a consequence there can be more nuanced planning and evaluation of malaria control programs than heretofore.

SUBMITTER: Castro MC

PROVIDER: S-EPMC4980052 | biostudies-literature | 2016 Aug

REPOSITORIES: biostudies-literature

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Malaria Incidence Rates from Time Series of 2-Wave Panel Surveys.

Castro Marcia C MC Maheu-Giroux Mathieu M Chiyaka Christinah C Singer Burton H BH

PLoS computational biology 20160810 8

Methodology to estimate malaria incidence rates from a commonly occurring form of interval-censored longitudinal parasitological data-specifically, 2-wave panel data-was first proposed 40 years ago based on the theory of continuous-time homogeneous Markov Chains. Assumptions of the methodology were suitable for settings with high malaria transmission in the absence of control measures, but are violated in areas experiencing fast decline or that have achieved very low transmission. No further dev ...[more]

PMID: 27509368

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Project description:ObjectiveDuring the COVID-19 pandemic, health system resources were reallocated to provide care for patients with COVID-19, limiting access for others. Patients themselves also constrained their visits to healthcare providers. In this study, we analysed the heterogeneous effects of the pandemic on the new diagnoses of lung, colorectal and breast cancer in Hungary.DesignTime series and panel models of quarterly administrative data, disaggregated by gender, age group and district of residence.ParticipantsData for the whole population of Hungary between the first quarter of 2017 and the second quarter of 2021.Main outcome measuresNumber of patients newly diagnosed with lung, colorectal and breast cancer, defined as those who were hospitalised with the appropriate primary International Classification of Diseases Tenth Revision diagnosis code but had not had hospital encounters with such a code within the previous 5 years.ResultsThe incidence of lung, colorectal and breast cancer decreased by 14.4% (95% CI 10.8% to 17.8%), 19.9% (95% CI 12.2% to 26.9%) and 15.5% (95% CI 2.5% to 27.0%), respectively, during the examined period of the pandemic, with different time patterns across cancer types. The incidence decreased more among people at least 65 years old than among the younger (p<0.05 for lung cancer and p<0.1 for colorectal cancer). At the district level, both the previously negative income gap in lung cancer incidence and the previously positive income gap in breast cancer incidence significantly narrowed during the pandemic (p<0.05).ConclusionsThe decline in new cancer diagnoses, caused by a combination of supply-side and demand-side factors, suggests that some cancer cases have remained hidden. It calls for action by policy makers to engage individuals with high risk of cancer more in accessing healthcare services, to diagnose the disease early and to prepare for effective management of patient pathways from diagnosis to survival or end-of-life care.

Dataset Information

Malaria Incidence Rates from Time Series of 2-Wave Panel Surveys.

Publications

Malaria Incidence Rates from Time Series of 2-Wave Panel Surveys.

Similar Datasets

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