From raw data to a score: Comparing quantitative methods that construct multi-level composite implementation strength scores of family planning programs in Malawi

Background: Data that capture implementation strength can be combined in multiple ways across content and health system levels to create a summary measure that can help us to explore and compare program implementation across facility catchment areas. Summary indices can make it easier for national policymakers to understand and address variation in strength of program implementation across jurisdictions. In this paper we describe development of an index that we used to describe the district level strength of implementation of the Malawi national family planning program. Methods: To develop the index, we used data collected during a 2017 national, health facility and community health worker Implementation Strength Assessment survey in Malawi to test different methods to combine indicators within and then across domains (4 methods: simple additive, weighted additive, principal components analysis, exploratory factor analysis) and combine scores across health facility and community health worker levels (2 methods: simple average and mixed effects model) to create a catchment area-level summary score for each health facility in Malawi. We explored how well each model captures variation and predicts couple years protection and how feasible it is to conduct each type of analysis and the resulting interpretability. Results: We found little difference in how the four methods combined indicator data at the individual and combined levels of the health system. However, there were major differences when combining scores across health system levels to obtain a score at the health facility catchment area level. The scores resulting from the mixed effects model were able to better discriminate differences between catchment area scores compared to the simple average method. The scores using the mixed effects combination method also demonstrated more of a dose and response relationship with couple years protection. Conclusions: The summary measure that was calculated from the mixed effects combination method captured the variation of strength of implementation of the Malawi national family planning program at the health facility catchment area level. However, the best method for creating an index should be based on pros and cons listed, not least, analyst capacity and ease of interpretability of findings. Ultimately, the resulting summary measure can aid decisionmakers in understanding the combined effect of multiple aspects of programs being implemented in their health system and comparing strengths of programs across geographies.

58 Integrating Quantitative Genetics and Epidemiology: Why Selection Against Infectious Diseases Is More Promising Than We Think

Pathogens have profound effects on livestock. The low heritabilities of individual binary disease status suggest limited prospects for genetic improvement. However, a proper quantitative genetic theory for infectious diseases, including transmission dynamics, is currently lacking. Here we present a quantitative genetic theory for endemic infectious diseases, focussing on the genetic factors that determine the prevalence (P; the mean fraction of the population that is infected). We present simple expressions for breeding values and genetic parameters for the prevalence. Without genetic variation in infectiousness, breeding values for prevalence are a factor 1/P greater than the ordinary breeding values for individual binary disease status (0/1). Hence, even though prevalence is the simple average of individual binary disease status, breeding values for prevalence show much greater variation than our ordinary breeding values. This implies that the genetic variance that determines the potential response of prevalence to selection is largely due to indirect genetic effects (IGE), and thus hidden to ordinary genetic analysis and selection. Hence, the genetic variance that determines the potential of livestock populations to respond to selection must be much greater than currently believed, particularly at low prevalence. We evaluated this implication using simulation of endemics following standard methods in epidemiology. Results show that response of prevalence to selection increases very strongly when prevalence decreases, and is much greater than predicted by our ordinary breeding values. These results supports our theoretical findings, and show that selection against infectious diseases is much more promising than currently believed.

Mathematically aggregating experts’ predictions of possible futures

Structured protocols offer a transparent and systematic way to elicit and combine/aggregate, probabilistic predictions from multiple experts. These judgements can be aggregated behaviourally or mathematically to derive a final group prediction. Mathematical rules (e.g., weighted linear combinations of judgments) provide an objective approach to aggregation. The quality of this aggregation can be defined in terms of accuracy, calibration and informativeness. These measures can be used to compare different aggregation approaches and help decide on which aggregation produces the “best” final prediction. When experts’ performance can be scored on similar questions ahead of time, these scores can be translated into performance-based weights, and a performance-based weighted aggregation can then be used. When this is not possible though, several other aggregation methods, informed by measurable proxies for good performance, can be formulated and compared. Here, we develop a suite of aggregation methods, informed by previous experience and the available literature. We differentially weight our experts’ estimates by measures of reasoning, engagement, openness to changing their mind, informativeness, prior knowledge, and extremity, asymmetry or granularity of estimates. Next, we investigate the relative performance of these aggregation methods using three datasets. The main goal of this research is to explore how measures of knowledge and behaviour of individuals can be leveraged to produce a better performing combined group judgment. Although the accuracy, calibration, and informativeness of the majority of methods are very similar, a couple of the aggregation methods consistently distinguish themselves as among the best or worst. Moreover, the majority of methods outperform the usual benchmarks provided by the simple average or the median of estimates.

Inclusiveness and the Progress of Indian States: Evidence from Inclusive Development Index Between 2011 and 2018

This article examines the progress of the Indian states in inclusiveness between 2011 and 2018, based on the “Inclusive Development Index” (IDI), which includes many important aspects of the economy and people. The study has followed the broad guidelines of the Organisation for Economic Co-operation and Development—OECD (2008) to construct IDI, and it is based on two pillars of growth—the process and the outcome. The index includes 26 sub-pillars represented by 104 indicators. The weights of the indicators are obtained separately for 2011 and 2018 by applying the principal component analysis at the indicator level, and then a simple average has been computed at the sub-pillar and pillar levels to obtain the composite IDI for the 19 major Indian states. The composite IDI shows that in 2018, while the most inclusive states are Himachal Pradesh, Tamil Nadu, Maharashtra, Karnataka, Gujarat, Chhattisgarh and Kerala, the least inclusive are the states of Rajasthan, Uttar Pradesh (UP), Madhya Pradesh (MP), Assam, Jharkhand and Bihar. The performance of the states, however, varies among pillars, sub-pillars and indicators in both 2011 and 2018. The study may help the states to identify their spheres of “low” performance and learn from their “front-runner” peers, so as to take the necessary policy initiatives.

Ranking methodology for Islamic banking sectors – modification of the conventional CAMELS method

The state of banking systems is an important issue. The purpose of this paper was to test whether the well-known CAMELS microeconomic methodology, generally used for ranking banks, is applicable to evaluating Islamic banking systems. The hypothesis was tested by implementing a method for a particular case, public, free data – from 2013 till the first quarter of 2018 – on Islamic banking systems from the “Islamic Financial Services Board” (IFBS) database. As expected, modifications were necessary. First, because of the lack of data (in Islamic databases, no data refer to the management (“M”)), and second, to avoid the subjectivity of the five-degree method and to reach more sensibility. Thus, a hundred-level (standardized) rating system was introduced – “CAELS 100”, where “100” refers to the levels. The other part of the methodology – creating a simple average of the (now level 100) rating of raw indicators to get the letters of CA(M)ELS in the relevant period – remained unchanged. After the data cleaning, only six countries (Bahrain, Egypt, Kuwait, Oman, Turkey, and the United Arab Emirates) were able to participate in the analysis.The result showed that Egypt, Turkey and Kuwait were the best ones respectively. Thus, it was concluded that this “CAELS 100” methodology is suitable for evaluating Islamic banking systems. AcknowledgmentThe research was supported by the project “Intelligent specialization program at Kaposvár University”, No. EFOP-3.6.1-16-2016-00007.

EVALUASI KEBIJAKAN PERSEDIAAN BAHAN BAKU KANTONG SEMEN UNTUK MENGURANGI BIAYA PERSEDIAAN (Studi Kasus: PT. SOLUSI BANGUN INDONESIA TBK).

This study aims to evaluate company policy in determining raw material ordering rates which are then compared with the EOQ, POQ, and Min-Max methods. This research uses a quantitive case study method using data obtained from the company. Forecasting is done using WinQSB and MAD, MSE and MAPE software for forecasting accuracy. Based on data processing, the data shows the horizontal pattern and the chosen forecasting method is the Simple Average method. Research shows the EOQ method has an order quantity of 1192 units / order with an order frequency of 11 times a year and has the smallest total inventory cost of the three methods compared which is Rp 269,520,852,781 or almost 50% lower than the total costs incurred by the company using the current method. ROP point has a value of 3395 units with a safety stock value of 106 units.AbstrakPenelitian ini bertujuan untuk mengevaluasi kebijakan perusahaan dalam menentukan tingkat pemesanan bahan baku yang kemudian dibandingkan dengan metode EOQ, POQ dan Min-Max. Penelitian ini menggunakan metode studi kasus kuantitatif dengan menggunakan data yang diperoleh dari perusahaan. Peramalan dilakukan menggunakan perangkat lunak WinQSB dan MAD, MSE dan MAPE untuk akurasi peramalan. Berdasarkan pengolahan data, data menunjukkan pola horizontal dan metode peramalan yang dipilih adalah metode Simple Average. Penelitian ini menunjukkan metode EOQ memiliki jumlah pesanan 1192 unit / pesanan dengan frekuensi pemesanan 11 kali setahun dan memiliki total biaya persediaan terkecil dari ketiga metode yang dibandingkan yaitu Rp 269.520.852 atau hampir 50% lebih rendah dari total biaya yang dikeluarkan oleh perusahaan dengan metode saat ini. Titik ROP memiliki nilai 3395 unit dengan nilai stok pengaman 106 unit.

Uterine cancer at a glance

Among gynecological tumors, malignant uterine tumor (MUT) is the 6th most common cancer in women and the 15th most common cancer overall. There were approximately 382 069 new cases and 89 929 deaths attributed to this type worldwide in 2018. Therefore, MUT was the second most common gynecological cancer and the fourth leading cause of death due to gynecological cancer in 2018, and is expected to increase the incidence rate by more than 50% globally by 2040. Mortality rates are lowest in Central and South Asia and most of Africa. Survivors of MUT may experience treatment-related issues, including infertility, early onset of menopause, sexual problems, and lower limb lymphedema. Wbuilds its own database from national modeling incidence estimates, using incidence ratios with a sampling method that relies on the calculation of a weighted or simple average of the most popular local rates applied to the population of a few regions or by an approximate estimate based on data provided by health establishments in neighboring countries. While in Algeria, existing statistical and epidemiological data and updated information on the pathology are insuffi cient. The objective of this work is to highlight the importance and the situation of the MUT in this country and to describe the different recent aspects (etiology, diagnostics and treatment) related to the disease.

MACHINE LEARNING PREDICTION FOR COVID 19 PANDEMIC IN INDIA

ABSTRACTBackgroundCoronavirus was detected in December 2019 in a bulk seafood shop in Wuhan, China. The original incident of COVID-19 pandemic in India was conveyed on 30th January 2020 instigating from the nation called china. As of 25th April 2020, the Ministry of Health and Family Welfare has established a total of 24, 942 incidents, 5, 210 recuperation including 1 relocation, and 779 demises in the republic.ObjectiveThe objective of the paper is to formulate a simple average aggregated machine learning method to predict the number, size, and length of COVID-19 cases extent and wind-up period crosswise India.MethodThis study examined the datasets via the Autoregressive Integrated Moving Average Model (ARIMA). The study also built a simple mean aggregated method established on the performance of 3 regression techniques such as Support Vector Regression (SVR, NN, and LR), Neural Network, and Linear Regression.ResultThe results showed that COVID-19 disease can correctly be predicted. The result of the prediction shows that COVID-19 ailment could be conveyed through water and air ecological variables and so preventives measures such as social distancing, wearing of mask and hand gloves, staying at home can help to avert the circulation of the sickness thereby resulting in reduced active cases and even mortality.ConclusionIt was established that the projected method outperformed when likened to previously obtainable practical models on the bases of prediction precision. Hence, putting in place the preventive measures can effectively manage the spread of COVID-19, and also the death rate will be reduced and eventually be over in India and other nations.