scholarly journals Indirect estimation of infant mortality in small areas

2019 ◽  
Vol 36 ◽  
pp. 1-37
Author(s):  
Ricardo Neupert ◽  
Rogelio Eduardo Fernandez Menjivar ◽  
Rogelio Eduardo Fernandez Castilla
Keyword(s):  
Infant Mortality ◽  
Estimation Methods ◽  
Random Errors ◽  
Indirect Methods ◽  
Essential Information ◽  
Indirect Estimation ◽  
Small Areas ◽  
Mortality Estimation ◽  
Robust Estimates ◽  
Mortality Estimates

The Brass-type indirect methods of early-age mortality estimation have been used for more than four decades, providing very robust estimates for countries without reliable vital registration systems. However, when estimation areas become smaller, the number of dead children could be very small, especially among those born to young women, who provide essential information to estimate recent mortality. In these cases, estimates could be affected by random errors and unexpected annual fluctuations. At the same time, although it is very unlikely that demographic trends in a small area would follow patterns very different from those prevailing in the broader environment they belong to, it is possible that some local events may become relevant to small areas, causing some deviations from the assumptions that may hold true to the larger area. The objective of this paper is to propose an adaptation of the indirect estimation approach, which would allow obtaining infant and child mortality estimates for small areas. As such, this proposal belongs to the realm of indirect estimation methods, sharing the limitations and advantages that characterize this type of estimation procedures. The method is illustrated with data from the 2014 Population and Housing Census of Myanmar. The results indicate that the method proposed here provides reliable and consistent infant mortality estimates, compared to the original Brass’ method, even in very small areas.

Can Indirect Estimation Methods and the Medical Officer of Health Reports 'Correct' Distorted Infant Mortality Rates Reported by the Registrar General? The Case of London, 1896–1911

2021 ◽  
pp. 57-81
Author(s):  
Sarah L Rafferty
Keyword(s):  
Infant Mortality ◽  
Medical Officer ◽  
Mortality Rates ◽  
Alternative Methods ◽  
Estimation Methods ◽  
Place Of Residence ◽  
Indirect Estimation ◽  
Registrar General ◽  
Estimation Techniques ◽  
The Rich

The Registrar General's Returns are an integral source for historical demographers. Concerns have been raised, however, over the geographical accuracy of their pre-1911 mortality figures when institutional deaths were not redistributed to place of residence. This paper determines the extent of the distortions caused by institutional mortality in the context of aggregate infant mortality rates for London's registration sub-districts. The potential of two alternative methods to 'correct' these distortions is then assessed. The first method uses indirect estimation techniques based on data from the 1911 Fertility Census, and the second exploits the rich detail available from the Medical Officer of Health reports. Through narrowing the focus to seven London registration sub-districts over the years 1896–1911, it is shown that both suggested alternative methods remove the institutional mortality biases found in the Registrar General's figures, yet they come with their own limitations.

scholarly journals Remote Sensing of Ecosystem Water Use Efficiency: A Review of Direct and Indirect Estimation Methods

2021 ◽  
Vol 13 (12) ◽  
pp. 2393
Author(s):  
Wanyuan Cai ◽  
Sana Ullah ◽  
Lei Yan ◽  
Yi Lin
Keyword(s):  
Remote Sensing ◽  
Water Use Efficiency ◽  
Analytical Model ◽  
Water Use ◽  
Estimation Methods ◽  
Retrieval Algorithm ◽  
Canopy Conductance ◽  
Coupling Mechanism ◽  
Indirect Methods ◽  
Use Efficiency

Water use efficiency (WUE) is a key index for understanding the ecosystem of carbon–water coupling. The undistinguishable carbon–water coupling mechanism and uncertainties of indirect methods by remote sensing products and process models render challenges for WUE remote sensing. In this paper, current progress in direct and indirect methods of WUE estimation by remote sensing is reviewed. Indirect methods based on gross primary production (GPP)/evapotranspiration (ET) from ground observation, processed models and remote sensing are the main ways to estimate WUE in which carbon and water cycles are independent processes. Various empirical models based on meteorological variables and remote sensed vegetation indices to estimate WUE proved the ability of remotely sensed data for WUE estimating. The analytical model provides a mechanistic opportunity for WUE estimation on an ecosystem scale, while the hypothesis has yet to be validated and applied for the shorter time scales. An optimized response of canopy conductance to atmospheric vapor pressure deficit (VPD) in an analytical model inverted from the conductance model has been also challenged. Partitioning transpiration (T) and evaporation (E) is a more complex phenomenon than that stated in the analytic model and needs a more precise remote sensing retrieval algorithm as well as ground validation, which is an opportunity for remote sensing to extrapolate WUE estimation from sites to a regional scale. Although studies on controlling the mechanism of environmental factors have provided an opportunity to improve WUE remote sensing, the mismatch in the spatial and temporal resolution of meteorological products and remote sensing data, as well as the uncertainty of meteorological reanalysis data, add further challenges. Therefore, improving the remote sensing-based methods of GPP and ET, developing high-quality meteorological forcing datasets and building mechanistic remote sensing models directly acting on carbon–water cycle coupling are possible ways to improve WUE remote sensing. Improvement in direct WUE remote sensing methods or remote sensing-driven ecosystem analysis methods can promote a better understanding of the global ecosystem carbon–water coupling mechanisms and vegetation functions–climate feedbacks to serve for the future global carbon neutrality.

scholarly journals Comparing Bayesian Spatial Conditional Overdispersion and the Besag–York–Mollié Models: Application to Infant Mortality Rates

Mathematics ◽  
2021 ◽  
Vol 9 (3) ◽  
pp. 282
Author(s):  
Mabel Morales-Otero ◽  
Vicente Núñez-Antón
Keyword(s):  
Infant Mortality ◽  
Count Data ◽  
Spatial Dependence ◽  
Poisson Model ◽  
Mortality Rates ◽  
Estimation Methods ◽  
Neighborhood Structure ◽  
Specific Context ◽  
Count Data Models ◽  
Conditional Mean

In this paper, we review overdispersed Bayesian generalized spatial conditional count data models. Their usefulness is illustrated with their application to infant mortality rates from Colombian regions and by comparing them with the widely used Besag–York–Mollié (BYM) models. These overdispersed models assume that excess of dispersion in the data may be partially caused from the possible spatial dependence existing among the different spatial units. Thus, specific regression structures are then proposed both for the conditional mean and for the dispersion parameter in the models, including covariates, as well as an assumed spatial neighborhood structure. We focus on the case of response variables following a Poisson distribution, specifically concentrating on the spatial generalized conditional normal overdispersion Poisson model. Models were fitted by making use of the Markov Chain Monte Carlo (MCMC) and Integrated Nested Laplace Approximation (INLA) algorithms in the specific context of Bayesian estimation methods.

scholarly journals Diurnal variation of leukocyte counts affects the indirect estimation of reference intervals

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Antje Torge ◽  
Rainer Haeckel ◽  
Mustafa Özcürümez ◽  
Alexander Krebs ◽  
Ralf Junker
Keyword(s):  
Diurnal Variation ◽  
Indirect Method ◽  
Venous Blood ◽  
Direct Methods ◽  
Reference Intervals ◽  
Indirect Methods ◽  
Indirect Estimation ◽  
Late Afternoon ◽  
Reference Limits ◽  
Leukocyte Counts

Abstract It has been observed that the estimation of reference intervals of leukocytes in whole venous blood leads to higher upper reference limits (uRLs) with indirect methods than has been reported in the literature determined by direct approaches. This phenomenon was reinvestigated with a newer, more advanced indirect method, and could be confirmed. Furthermore, a diurnal variation was observed with lower values during the morning and higher values in the late afternoon and at night. This observation can explain why indirect approaches using samples collected during 24 h lead to higher uRLs than direct methods applied on samples collected presumably in the morning.

A new indirect estimation of reference intervals: truncated minimum chi-square (TMC) approach

2019 ◽  
Vol 57 (12) ◽  
pp. 1933-1947 ◽  
Author(s):  
Werner Wosniok ◽  
Rainer Haeckel
Keyword(s):  
Detection Limit ◽  
Simulated Data ◽  
Reference Interval ◽  
Reference Intervals ◽  
Skewed Data ◽  
Chi Square ◽  
Indirect Methods ◽  
Indirect Estimation ◽  
Estimated Parameters ◽  
Data Files

Abstract All known direct and indirect approaches for the estimation of reference intervals (RIs) have difficulties in processing very skewed data with a high percentage of values at or below the detection limit. A new model for the indirect estimation of RIs is proposed, which can be applied even to extremely skewed data distributions with a relatively high percentage of data at or below the detection limit. Furthermore, it fits better to some simulated data files than other indirect methods. The approach starts with a quantile-quantile plot providing preliminary estimates for the parameters (λ, μ, σ) of the assumed power normal distribution. These are iteratively refined by a truncated minimum chi-square (TMC) estimation. The finally estimated parameters are used to calculate the 95% reference interval. Confidence intervals for the interval limits are calculated by the asymptotic formula for quantiles, and tolerance limits are determined via bootstrapping. If age intervals are given, the procedure is applied per age interval and a spline function describes the age dependency of the reference limits by a continuous function. The approach can be performed in the statistical package R and on the Excel platform.

scholarly journals Age Distribution, Trends, and Forecasts of Under-5 Mortality in Sub-Saharan Africa

2018 ◽  
Author(s):  
Iván Mejía-Guevara ◽  
Wenyun Zuo ◽  
Eran Bendavid ◽  
Nan Li ◽  
Shripad Tuljapurkar
Keyword(s):  
Sustainable Development ◽  
Child Mortality ◽  
Age Distribution ◽  
Sub Saharan Africa ◽  
Death Rates ◽  
The Sustainable Development ◽  
Mortality Estimation ◽  
Age Patterns ◽  
Sub Saharan ◽  
Mortality Estimates

AbstractBackgroundDespite the sharp decline in global under-5 deaths since 1990, uneven progress has been achieved across and within countries. In Sub-Saharan Africa, the Millennium Development Goals targets for child mortality were met only by a few countries, and recently new targets were set in goals for Sustainable Development that include the eradication of preventable deaths by reducing neonatal and under-5 mortality rates to at least as low 12 and 25 per 1000 live births by 2030, respectively. As the reduction of preventable deaths has a direct impact on their age distribution, the foci of this study are assessing age patterns, trends over time, and forecasts of mortality rates in Sub-Saharan Africa.Methods and findingsData came from 104 nationally-representative Demographic and Health Surveys with full birth histories from 31 Sub-Saharan African countries from 1990 to 2016 (a total of 448 country-years of data). We assessed the distribution of age at death through the following demographic model. First, we used a direct method for the estimation of death rates with full-birth histories from survey data to construct age profiles of under-5 mortality on a monthly basis. Second, a two-dimensional P-spline approach was used to smooth out raw estimates of death rates by age and time. Third, a variant of the Lee-Carter model, designed for populations with limited data, was used to fit and forecast age profiles of mortality. We used mortality estimates from the United Nations Inter-agency group for Child Mortality Estimation to adjust, validate and minimize the risk of bias in survival, truncation, and recall in mortality estimation.Our study has three salient findings. First, we observe a monotonous decline of death rates at every age in most countries, but with notable differences in the age-patterns over time. Second, our projections of continued decline of child mortality differ from existing estimates from the United Nations Inter-agency group for Child Mortality Estimation in 5 countries for both neonatal and under-5 mortality. Finally, we predict that only 5 countries (Guinea, Liberia, Rwanda, Tanzania, and Uganda) are on track to achieve the sustainable development goal targets on child mortality by 2030. Poor data quality issues that include bias in the report of births and deaths, or age heaping, remain a limitation of this study.ConclusionsThis study is the first to combine full birth history data and mortality estimates from external reliable sources to model age patterns of under-5 mortality across time in Sub-Saharan Africa. We demonstrate that countries with a rapid pace of mortality reduction across ages would be more likely to achieve the sustainable development goal targets of child mortality reduction. Our mortality model predicts that if neonatal and under-5 deaths decline at the rates observed during the last 25 years, only 5 countries would reach those targets by 2030, 15 would achieve them between 2030 and 2050, and 11 afterwards.

scholarly journals Mark-recapture vs. line-transect abundance estimates of a coastal dolphin population: a case study of Tursiops truncatus from Laguna, southern Brazil

2017 ◽  
Vol 11 (1-2) ◽  
pp. 133-143 ◽  
Author(s):  
Fábio G. Daura-Jorge ◽  
Paulo César Simões-Lopes
Keyword(s):  
Anthropogenic Impacts ◽  
Bottlenose Dolphins ◽  
A Priori ◽  
Distance Sampling ◽  
Estimation Methods ◽  
Line Transect ◽  
Southern Brazil ◽  
Mark Recapture ◽  
Pilot Studies ◽  
Robust Estimates

Cetacean populations in coastal habitats are increasingly threatened by multiple anthropogenic impacts. Monitoring these populations to obtain robust estimates of abundance and detect trends over time is critical to achieve conservation goals. Here, we conducted a pilot study to evaluate the effectiveness of two commonly used abundance estimation methods: mark-recapture and distance sampling line-transect. Surveys were conducted to estimate the abundance of bottlenose dolphins in Laguna, southern Brazil. We implemented power-analysis models and compared both techniques in terms of cost, time and effectiveness to detect trends over a five-year period. Mark-recapture models were analyzed in MARK and resulted in an abundance of 50 individuals (CI = 39-64) with a coefficient of variation (CV) of 0.13. The line-transect models were implemented using the program DISTANCE and resulted in an estimate of 62 individuals (CI = 38-103), with a CV of 0.24. Comparing both approaches, mark-recapture resulted 1.30 time more expensive than line-transect for a single season of effort, but was twice as effective in terms of precision. As a consequence, the probability of detecting a 5% trend during a five-year period is 2.08 times higher with mark recapture. Conversely, the final cost to detect a trend with distance sampling is 1.19 time higher but considering six more years of effort. These results highlight the importance of selecting a-priori sampling design techniques that include developing pilot studies that evaluate the bias, precision and accuracy of estimates while considering costs involved. Considering the small population size estimated herein, the sensitivity of both approaches for detecting trends is not sufficient because the original population would be markedly reduced by the time a declining trend was detected. Thus, a precautionary approach is still imperative, even when robust estimates are obtained.

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