This document provides an actuarial analysis of including tuberculosis (TB) coverage in the Lagos State Health Scheme in Nigeria. It analyzes 3 different TB treatment regimens and estimates the additional premium required. Based on historical TB case data from 2013-2016, it projects the number of cases and costs for the next 3 years. The analysis finds the additional premium to be 488.79 Naira on average per person to cover TB screening tests and the 3 treatment regimens. It acknowledges limitations in the source data and outlines key assumptions made in the projections.
Descriptive Analysis of Malaria Surveillance Data of Belaichari Upazila Healt...Dr. Habibur Rahim
A malaria case can be defined as a patient having febrile period within 48 hours (Temperature ≥ 37.5°C) associated with clinical symptoms like headache, chills, severe malaise, severe weakness, vomiting etc. at the time of examination or within 48 hours and also confirmation of presence of Plasmodium Vivax or P. Falciparum in Blood slide examination (BSE) or Rapid Diagnostic Test (RDT) test. The Analysis of public health surveillance data on Malaria has been conducted in Upazila health complex of Belaichari of Rangamati hill tracts. Study duration was 10 days dated from 22-11-2018 to 03-12-2018. Data collected from monthly submitted data of web based surveillance of National Malaria Control Program (NMCP) website MIS, DHIS2, hospital Registry with the help of honorable UHFPO and Statistician and other related staffs also. Data of last four months (from July-October, 2018) taken for this simple analysis from monthly web based surveillance of NMCP, MIS. This data set has been taken to analyze the distribution of Malaria according to Age, sex, Time, place, during the study period. To find out the susceptibility and trend of this disease by appropriate analysis and interpretation of data. This study also given a look on the comparison of performance of GoB and NGO work to make a clear view. This study shows that incidence of malaria was high in July, 2018 as it was in monsoon season, and people above 15 years old are more affected, where male are more in ratio as they work in forests and outside of home. The Farua Union is riskier for malaria infection as it carries boundary with India and Myanmar territory. Plasmodium falciparum is the most infective parasite at Belaichari as it causes about 89% of total Malaria cases. In comparison with the previous year cases this year rate of infection of malaria is decreasing. It’s a matter of hope that it will guide us to walk through the way of Malaria elimination program in the next decade. The study was confined only in analysis of data of four months. It’s not reflective for the criteria of disease distribution round the year or the criteria of Malaria in the hill tracts area at all. Big scale analysis of data is recommended to be conducted for public health interest.
Non-invasive Diagnostic Tools: Cardiometabolic Risk Assessment and Predictionasclepiuspdfs
Cardiometabolic risks (CMRs) have rapidly increased to epidemic proportions worldwide in the past three decades. Cardiovascular disease (CVD) remains the number one killer. No country has reduced, reversed, or prevented the increase in the incidence or prevalence of chronic metabolic diseases. Framingham Heart Study group described the modifiable risk factors that promote the development of CVD. They also developed risk calculators, for the prediction of acute vascular events such as heart attacks and stroke. The risk predictor algorithms were fine-tuned, as and when additional risk factors were discovered. However, at the time of this writing, there is no such calculator for assessment, stratification, and management of CMRs. On the other hand, numbers of non-invasive diagnostic devices have been developed for continuous monitoring of blood pressure and glucose profiles. We have described in our earlier articles, non-invasive diagnostic platform developed by LD-Technologies,
Descriptive Analysis of Malaria Surveillance Data of Belaichari Upazila Healt...Dr. Habibur Rahim
A malaria case can be defined as a patient having febrile period within 48 hours (Temperature ≥ 37.5°C) associated with clinical symptoms like headache, chills, severe malaise, severe weakness, vomiting etc. at the time of examination or within 48 hours and also confirmation of presence of Plasmodium Vivax or P. Falciparum in Blood slide examination (BSE) or Rapid Diagnostic Test (RDT) test. The Analysis of public health surveillance data on Malaria has been conducted in Upazila health complex of Belaichari of Rangamati hill tracts. Study duration was 10 days dated from 22-11-2018 to 03-12-2018. Data collected from monthly submitted data of web based surveillance of National Malaria Control Program (NMCP) website MIS, DHIS2, hospital Registry with the help of honorable UHFPO and Statistician and other related staffs also. Data of last four months (from July-October, 2018) taken for this simple analysis from monthly web based surveillance of NMCP, MIS. This data set has been taken to analyze the distribution of Malaria according to Age, sex, Time, place, during the study period. To find out the susceptibility and trend of this disease by appropriate analysis and interpretation of data. This study also given a look on the comparison of performance of GoB and NGO work to make a clear view. This study shows that incidence of malaria was high in July, 2018 as it was in monsoon season, and people above 15 years old are more affected, where male are more in ratio as they work in forests and outside of home. The Farua Union is riskier for malaria infection as it carries boundary with India and Myanmar territory. Plasmodium falciparum is the most infective parasite at Belaichari as it causes about 89% of total Malaria cases. In comparison with the previous year cases this year rate of infection of malaria is decreasing. It’s a matter of hope that it will guide us to walk through the way of Malaria elimination program in the next decade. The study was confined only in analysis of data of four months. It’s not reflective for the criteria of disease distribution round the year or the criteria of Malaria in the hill tracts area at all. Big scale analysis of data is recommended to be conducted for public health interest.
Non-invasive Diagnostic Tools: Cardiometabolic Risk Assessment and Predictionasclepiuspdfs
Cardiometabolic risks (CMRs) have rapidly increased to epidemic proportions worldwide in the past three decades. Cardiovascular disease (CVD) remains the number one killer. No country has reduced, reversed, or prevented the increase in the incidence or prevalence of chronic metabolic diseases. Framingham Heart Study group described the modifiable risk factors that promote the development of CVD. They also developed risk calculators, for the prediction of acute vascular events such as heart attacks and stroke. The risk predictor algorithms were fine-tuned, as and when additional risk factors were discovered. However, at the time of this writing, there is no such calculator for assessment, stratification, and management of CMRs. On the other hand, numbers of non-invasive diagnostic devices have been developed for continuous monitoring of blood pressure and glucose profiles. We have described in our earlier articles, non-invasive diagnostic platform developed by LD-Technologies,
HSA 535 Week 1 Discussion 1 -
CDC and BMA" Please respond to the following:
From the first two (2) e-Activities, give a synopsis of the various challenges facing health care professionals, and determine whether or not you believe these professionals can formulate predictive plans from both agencies. Be specific, giving supporting rationales for your observations.
For more classes visit
www.snaptutorial.com
HSA 535 Week 1 Discussion 1 -
CDC and BMA" Please respond to the following:
From the first two (2) e-Activities, give a synopsis of the various challenges facing health care professionals, and
For more classes visit
www.snaptutorial.com
HSA 535 Week 1 Discussion 1 -
CDC and BMA" Please respond to the following:
From the first two (2) e-Activities, give a synopsis of the various challenges facing health care professionals, and determine whether or not you believe these professionals can formulate predictive plans from both agencies. Be specific, giving supporting rationales for your observations.
Cost-benefit analysis of Medication Assisted Treatment and Needle-Syringe Pro...Irma Kirtadze M.D.
This presentation was produced by Addiction Research Center Alternative Georgia for the Addiction Research Development in Georgia Project funded by United States Agency for International Development (USAID) and Czech Development Agency (CzDA).
HSA 535 Week 1 Discussion 1 -
CDC and BMA" Please respond to the following:
From the first two (2) e-Activities, give a synopsis of the various challenges facing health care professionals, and determine whether or not you believe these professionals can formulate predictive plans from both agencies. Be specific, giving supporting rationales for your observations.
From the third e-Activity, give a comprehensive critiqued evaluation of your state’s DOH disease-management protocols. Also, from the analysis of the case study, determine if your state’s standpoint on the disease is adequate. Be specific, articulating the actions that can be taken to improve your state’s DOH.
HSA 535 Effective Communication - tutorialrank.comBartholomew42
For more course tutorials visit
www.tutorialrank.com
HSA 535 Week 1 Discussion 1 -
CDC and BMA" Please respond to the following:
From the first two (2) e-Activities, give a synopsis of the various challenges facing health care professionals, and determine whether or not you believe these professionals can formulate predictive plans from both agencies. Be specific, giving supporting rationales for your observations.
From the third e-Activity, give a comprehensive critiqued ev
A presentation for undergrad students visited Wolrd Health Organization (WHO) to understand what universal health coverage (UHC) is and how WHO works for UHC.
Data Driven Decision Making in Ministry of Health and Family WelfareData Portal India
Data Driven Decision Making in Ministry of Health and Family Welfare presentation by Dr. Vishnu Kant Srivastava, Chief Director D/o Health & Family Welfare.
International Journal of Mathematics and Statistics Invention (IJMSI) is an international journal intended for professionals and researchers in all fields of computer science and electronics. IJMSI publishes research articles and reviews within the whole field Mathematics and Statistics, new teaching methods, assessment, validation and the impact of new technologies and it will continue to provide information on the latest trends and developments in this ever-expanding subject. The publications of papers are selected through double peer reviewed to ensure originality, relevance, and readability. The articles published in our journal can be accessed online.
COVID-19 data configuration and statistical analysisAnshJAIN50
The following report aims to identify the primary factors influencing the spread of Covid-19. To do this, I have analyzed the rate of spread in MEDCs and LEDCs - countries differing significantly in development. MEDCs, being more economically developed, tend to have superior healthcare, higher life expectancy, and generally better infrastructure, contrasting with LEDCs. This report aims to understand whether the characteristics of MEDCs and LEDCs can significantly impact the rate of spread of Covid-19, as well as more obscure factors that could have a greater impact than previously thought. In this report we will be examining 3 different MEDCs and LEDCs to develop a clear conclusion on whether we believe a country's development correlates to the rate of spread of Covid-19.
How a U.S. COVID-19 Data Registry Fuels Global ResearchHealth Catalyst
In addition to driving COVID-19 understanding within the United States, a national disease registry is informing research beyond U.S. borders. Clinicians with the Singapore Ministry of Healthcare Office for Healthcare Transformation (MOHT) have used Health Catalyst Touchstone® COVID-19 data to develop a machine learning tool that helps predict the likelihood of COVID-19 mortality. With this national data set that leverages deep aggregated EHR data, the MOHT accessed the research-grade data it needed to build a machine-learning algorithm that predicts risk of death from COVID-19. The registry-informed prediction model was accurate enough to stand up to comparisons in the published literature and promises to help inform vaccine research and, ultimately, allocation of vaccines within populations.
HSA 535 Week 1 Discussion 1 -
CDC and BMA" Please respond to the following:
From the first two (2) e-Activities, give a synopsis of the various challenges facing health care professionals, and determine whether or not you believe these professionals can formulate predictive plans from both agencies. Be specific, giving supporting rationales for your observations.
For more classes visit
www.snaptutorial.com
HSA 535 Week 1 Discussion 1 -
CDC and BMA" Please respond to the following:
From the first two (2) e-Activities, give a synopsis of the various challenges facing health care professionals, and
For more classes visit
www.snaptutorial.com
HSA 535 Week 1 Discussion 1 -
CDC and BMA" Please respond to the following:
From the first two (2) e-Activities, give a synopsis of the various challenges facing health care professionals, and determine whether or not you believe these professionals can formulate predictive plans from both agencies. Be specific, giving supporting rationales for your observations.
Cost-benefit analysis of Medication Assisted Treatment and Needle-Syringe Pro...Irma Kirtadze M.D.
This presentation was produced by Addiction Research Center Alternative Georgia for the Addiction Research Development in Georgia Project funded by United States Agency for International Development (USAID) and Czech Development Agency (CzDA).
HSA 535 Week 1 Discussion 1 -
CDC and BMA" Please respond to the following:
From the first two (2) e-Activities, give a synopsis of the various challenges facing health care professionals, and determine whether or not you believe these professionals can formulate predictive plans from both agencies. Be specific, giving supporting rationales for your observations.
From the third e-Activity, give a comprehensive critiqued evaluation of your state’s DOH disease-management protocols. Also, from the analysis of the case study, determine if your state’s standpoint on the disease is adequate. Be specific, articulating the actions that can be taken to improve your state’s DOH.
HSA 535 Effective Communication - tutorialrank.comBartholomew42
For more course tutorials visit
www.tutorialrank.com
HSA 535 Week 1 Discussion 1 -
CDC and BMA" Please respond to the following:
From the first two (2) e-Activities, give a synopsis of the various challenges facing health care professionals, and determine whether or not you believe these professionals can formulate predictive plans from both agencies. Be specific, giving supporting rationales for your observations.
From the third e-Activity, give a comprehensive critiqued ev
A presentation for undergrad students visited Wolrd Health Organization (WHO) to understand what universal health coverage (UHC) is and how WHO works for UHC.
Data Driven Decision Making in Ministry of Health and Family WelfareData Portal India
Data Driven Decision Making in Ministry of Health and Family Welfare presentation by Dr. Vishnu Kant Srivastava, Chief Director D/o Health & Family Welfare.
International Journal of Mathematics and Statistics Invention (IJMSI) is an international journal intended for professionals and researchers in all fields of computer science and electronics. IJMSI publishes research articles and reviews within the whole field Mathematics and Statistics, new teaching methods, assessment, validation and the impact of new technologies and it will continue to provide information on the latest trends and developments in this ever-expanding subject. The publications of papers are selected through double peer reviewed to ensure originality, relevance, and readability. The articles published in our journal can be accessed online.
COVID-19 data configuration and statistical analysisAnshJAIN50
The following report aims to identify the primary factors influencing the spread of Covid-19. To do this, I have analyzed the rate of spread in MEDCs and LEDCs - countries differing significantly in development. MEDCs, being more economically developed, tend to have superior healthcare, higher life expectancy, and generally better infrastructure, contrasting with LEDCs. This report aims to understand whether the characteristics of MEDCs and LEDCs can significantly impact the rate of spread of Covid-19, as well as more obscure factors that could have a greater impact than previously thought. In this report we will be examining 3 different MEDCs and LEDCs to develop a clear conclusion on whether we believe a country's development correlates to the rate of spread of Covid-19.
How a U.S. COVID-19 Data Registry Fuels Global ResearchHealth Catalyst
In addition to driving COVID-19 understanding within the United States, a national disease registry is informing research beyond U.S. borders. Clinicians with the Singapore Ministry of Healthcare Office for Healthcare Transformation (MOHT) have used Health Catalyst Touchstone® COVID-19 data to develop a machine learning tool that helps predict the likelihood of COVID-19 mortality. With this national data set that leverages deep aggregated EHR data, the MOHT accessed the research-grade data it needed to build a machine-learning algorithm that predicts risk of death from COVID-19. The registry-informed prediction model was accurate enough to stand up to comparisons in the published literature and promises to help inform vaccine research and, ultimately, allocation of vaccines within populations.
ANALYSIS OF COVID-19 IN THE UNITED STATES USING MACHINE LEARNINGmlaij
The unprecedented outbreak of COVID-19 also known as the coronavirus has caused a pandemic like none
ever seen before this century. Its impact has been massive on a global level. The deadly virus has
commanded nations around the world to increase their efforts to fight against the spread of the virus after
the stress it has put on resources. With the number of new cases increasing day by day around the world,
the objective of this paper is to contribute towards the analysis of the virus by leveraging machine learning
models to understand its behavior and predict future patterns in the United States (US) based on data
obtained from the COVID-19 Tracking Project.
Analysis of Covid-19 in the United States using Machine Learningmlaij
The unprecedented outbreak of COVID-19 also known as the coronavirus has caused a pandemic like none ever seen before this century. Its impact has been massive on a global level. The deadly virus has commanded nations around the world to increase their efforts to fight against the spread of the virus after the stress it has put on resources. With the number of new cases increasing day by day around the world, the objective of this paper is to contribute towards the analysis of the virus by leveraging machine learning models to understand its behavior and predict future patterns in the United States (US) based on data obtained from the COVID-19 Tracking Project.
Measuring performance on the Healthcare Access and
Quality Index for 195 countries and territories and selected
subnational locations: a systematic analysis from the Global
Burden of Disease Study 2016
Test positivity – Evaluation of a new metric to assess epidemic dispersal med...Olutosin Ademola Otekunrin
Epidemic control may be hampered when the percentage of asymptomatic cases is high. Seeking remedies for this problem, test positivity was explored between the first 60 to 90 epidemic days in six countries that reported their first COVID-19 case between February and March 2020: Argentina, Bolivia, Chile, Cuba, Mexico, and Uruguay.
Test positivity (TP) is the percentage of test-positive individuals reported on a given day out of all individuals tested the same day. To generate both country-specific and multi-country information, this study was implemented in two stages. First, the epidemiologic data of the country infected last (Uruguay) were analyzed. If at
least one TP-related analysis yielded a statistically significant relationship, later assessments would investigate the six countries. The Uruguayan data indicated (i) a positive correlation between daily TP and daily new cases (r = 0.75); (ii) a negative correlation between TP and the number of tests conducted per million inhabitants (TPMI, r = 0.66); and (iii) three temporal stages, which differed from one another in both TP and TPMI medians (p < 0.01) and, together, revealed a negative relationship between TPMI and TP. No significant relationship
was found between TP and the number of active or recovered patients. The six countries showed a positive correlation between TP and the number of deaths/million inhabitants (DMI, r = 0.65, p < 0.01). With one exception –a country where isolation was not pursued , all countries showed a negative correlation between
TP and TPMI (r = 0.74). The temporal analysis of country-specific policies revealed four patterns, characterized by: (1) low TPMI and high DMI, (2) high TPMI and low DMI; (3) an intermediate pattern, and (4) high TPMI and
high DMI. Findings support the hypothesis that test positivity may guide epidemiologic policy-making, provided that policy-related factors are considered and high-resolution geographical data are utilized.
What factors explain the fertility transition in India?HFG Project
The purpose of this study is to explain the main causes of fertility change and its implications in India over the time period 1998 to 2016. To accomplish this, we first test the proximate determinants model to see if it is valid in the Indian context and then use it to estimate the contribution of each determinant to changes in India’s total fertility rate. The findings are intended to inform program managers, donors, and researchers about the link between contraceptive prevalence rate (CPR) and fertility decline.
A benefits case study describing how national stakeholders have used HSCIC's immunisation statistics to help drive improvements in immunisation services and inform decisions when managing disease outbreaks
A Survey and Analysis on Classification and Regression Data Mining Techniques...theijes
Classification and regression as data mining techniques for predicting the diseases outbreak has been permitted in the health institutions which have relative opportunities for conducting the treatment of diseases. But there is a need to develop a strong model for predicting disease outbreak in datasets based in various countries by filling the existing data mining technique gaps where the majority of models are relaying on single data mining techniques which their accuracies in prediction are not maximized for achieving expected results and also prediction are still few. This paper presents a survey and analysis for existing techniques on both classification and regression models techniques that have been applied for diseases outbreak prediction in datasets.
Many ways to support street children.pptxSERUDS INDIA
By raising awareness, providing support, advocating for change, and offering assistance to children in need, individuals can play a crucial role in improving the lives of street children and helping them realize their full potential
Donate Us
https://serudsindia.org/how-individuals-can-support-street-children-in-india/
#donatefororphan, #donateforhomelesschildren, #childeducation, #ngochildeducation, #donateforeducation, #donationforchildeducation, #sponsorforpoorchild, #sponsororphanage #sponsororphanchild, #donation, #education, #charity, #educationforchild, #seruds, #kurnool, #joyhome
What is the point of small housing associations.pptxPaul Smith
Given the small scale of housing associations and their relative high cost per home what is the point of them and how do we justify their continued existance
Presentation by Jared Jageler, David Adler, Noelia Duchovny, and Evan Herrnstadt, analysts in CBO’s Microeconomic Studies and Health Analysis Divisions, at the Association of Environmental and Resource Economists Summer Conference.
Jennifer Schaus and Associates hosts a complimentary webinar series on The FAR in 2024. Join the webinars on Wednesdays and Fridays at noon, eastern.
Recordings are on YouTube and the company website.
https://www.youtube.com/@jenniferschaus/videos
A process server is a authorized person for delivering legal documents, such as summons, complaints, subpoenas, and other court papers, to peoples involved in legal proceedings.
Up the Ratios Bylaws - a Comprehensive Process of Our Organizationuptheratios
Up the Ratios is a non-profit organization dedicated to bridging the gap in STEM education for underprivileged students by providing free, high-quality learning opportunities in robotics and other STEM fields. Our mission is to empower the next generation of innovators, thinkers, and problem-solvers by offering a range of educational programs that foster curiosity, creativity, and critical thinking.
At Up the Ratios, we believe that every student, regardless of their socio-economic background, should have access to the tools and knowledge needed to succeed in today's technology-driven world. To achieve this, we host a variety of free classes, workshops, summer camps, and live lectures tailored to students from underserved communities. Our programs are designed to be engaging and hands-on, allowing students to explore the exciting world of robotics and STEM through practical, real-world applications.
Our free classes cover fundamental concepts in robotics, coding, and engineering, providing students with a strong foundation in these critical areas. Through our interactive workshops, students can dive deeper into specific topics, working on projects that challenge them to apply what they've learned and think creatively. Our summer camps offer an immersive experience where students can collaborate on larger projects, develop their teamwork skills, and gain confidence in their abilities.
In addition to our local programs, Up the Ratios is committed to making a global impact. We take donations of new and gently used robotics parts, which we then distribute to students and educational institutions in other countries. These donations help ensure that young learners worldwide have the resources they need to explore and excel in STEM fields. By supporting education in this way, we aim to nurture a global community of future leaders and innovators.
Our live lectures feature guest speakers from various STEM disciplines, including engineers, scientists, and industry professionals who share their knowledge and experiences with our students. These lectures provide valuable insights into potential career paths and inspire students to pursue their passions in STEM.
Up the Ratios relies on the generosity of donors and volunteers to continue our work. Contributions of time, expertise, and financial support are crucial to sustaining our programs and expanding our reach. Whether you're an individual passionate about education, a professional in the STEM field, or a company looking to give back to the community, there are many ways to get involved and make a difference.
We are proud of the positive impact we've had on the lives of countless students, many of whom have gone on to pursue higher education and careers in STEM. By providing these young minds with the tools and opportunities they need to succeed, we are not only changing their futures but also contributing to the advancement of technology and innovation on a broader scale.
Russian anarchist and anti-war movement in the third year of full-scale warAntti Rautiainen
Anarchist group ANA Regensburg hosted my online-presentation on 16th of May 2024, in which I discussed tactics of anti-war activism in Russia, and reasons why the anti-war movement has not been able to make an impact to change the course of events yet. Cases of anarchists repressed for anti-war activities are presented, as well as strategies of support for political prisoners, and modest successes in supporting their struggles.
Thumbnail picture is by MediaZona, you may read their report on anti-war arson attacks in Russia here: https://en.zona.media/article/2022/10/13/burn-map
Links:
Autonomous Action
http://Avtonom.org
Anarchist Black Cross Moscow
http://Avtonom.org/abc
Solidarity Zone
https://t.me/solidarity_zone
Memorial
https://memopzk.org/, https://t.me/pzk_memorial
OVD-Info
https://en.ovdinfo.org/antiwar-ovd-info-guide
RosUznik
https://rosuznik.org/
Uznik Online
http://uznikonline.tilda.ws/
Russian Reader
https://therussianreader.com/
ABC Irkutsk
https://abc38.noblogs.org/
Send mail to prisoners from abroad:
http://Prisonmail.online
YouTube: https://youtu.be/c5nSOdU48O8
Spotify: https://podcasters.spotify.com/pod/show/libertarianlifecoach/episodes/Russian-anarchist-and-anti-war-movement-in-the-third-year-of-full-scale-war-e2k8ai4
2. Lagos State Health Scheme: Supplementary Actuarial Analysis of Tuberculosis (TB)
1 HFG, Nigeria – Abt Associates
EXECUTIVE SUMMARY
Our focus in this report is to actuarially estimate the medical cost of including tuberculosis (TB) in the total benefit
structure.
We have considered modular pricing under 3 different regimens:
Regimen I - Drug susceptible TB cases of Kids (pediatrics)
Regimen II - Drug susceptible TB cases of adults
Regimen III - Shorter Regimen (DRTB)
The pure premium estimate under the three regimens above are presented in the table below:
Table 1: Modular pricing for three (3) TB regimens
This work was funded with support from the U.S. Agency for International Development
(USAID) as part of the Health Finance and Governance (HFG) project led by Abt Associates
under USAID cooperative agreement AID-OAA-A-12-00080. The contents are the
responsibility of Abt Associates and do not necessarily reflect the views of USAID or the United
States Government.
Additional Risk premium for TB cover Projected amount in Naira
GeneXpert Test 92.64
Sputum Test I 9.97
Sputum Test II 9.97
Sputum Test III 9.97
Regimen I - DSTB for (Kids - Pediatrics) 10.92
Regimen II - DSTB for others 78.59
Regimen III - DRTB for All 276.74
Total Cost for additional TB Cover 488.79
3. Lagos State Health Scheme: Supplementary Actuarial Analysis of Tuberculosis (TB)
1 HFG, Nigeria – Abt Associates
Table of Contents
EXECUTIVE SUMMARY ...............................................................................................................................................1
1. Introduction..................................................................................................................................................2
2. Pricing and Methodology Assumptions Data ..................................................................................................4
3. Results .........................................................................................................................................................7
4. Sensitivity Analysis........................................................................................................................................9
5. Further Sensitivity and Scenario Analysis .....................................................................................................10
6. Conclusions................................................................................................................................................11
7. Appendix ....................................................................................................................................................12
4. Lagos State Health Scheme: Supplementary Actuarial Analysis of Tuberculosis (TB)
2 HFG, Nigeria – Abt Associates
1. Introduction
USAID’s Health Finance and Governance Project contracted Ernst & Young, to carry out an actuarial study of the medical
cost of Tuberculosis (TB) as a benefit in an insurance scheme. This analysis also forms part of the main actuarial study
being conducted on the proposed benefit package for the Lagos State Health Scheme (LSHS).
1.1 Scope of Works
By the terms of reference, the works cover;
Carrying out an actuarial analysis to determine the financial impact of adding TB to the Lagos State Health
Scheme benefit package, i.e. advise on the additional risk premium to cover TB.
Modular pricing for TB cover structured along;
o Testing
o Treatment, which is further segmented into costs for;
Drug Susceptible (DS) – paediatrics
Drug Susceptible (DS) – adults
Drug Resistant (DR)
1.2 Target Market
The Lagos State Health Scheme is intended to be a mandatory insurance scheme to cover the entire population of the
state.Ourunderstandingisthat,atinception,theprogrammaycommencewiththeenrolmentofLagosStategovernment
workers as well as pregnant women and children under 5 years of age.
We have assumed a take-up rate of 10% of the entire population takes up the insurance in this analysis and also
demonstrate the impact of a 100% take-up.
1.3 Actuarial Data and Limitations
The State’s TB co-ordination office provided us with statistics from the National TB and Leprosy Control Program reports
on case finding. The report is specific to Lagos State and covers all 20 LGA’s. The same office also provided us with the
cost of treatment per patient for each regimen.
There are limitations within the data, some of which include;
DS and DR cases have not been explicitly specified in the total number of cases registered in the year. We have
estimated the number of DR cases as 4.3% of new TB cases, and 25% of previously treated [World Health
Organisation.GlobalTuberculosis Control:WHOreport2016.Geneva,Switzerland:World HealthOrganisation,
2016].
The data format for years 2013 through to 2015 is not consistent with the format of the most recent review
5. Lagos State Health Scheme: Supplementary Actuarial Analysis of Tuberculosis (TB)
3 HFG, Nigeria – Abt Associates
year (2016).
The TB prevalence rate in Nigeria is 322 out of 100 000 lives in Nigeria according to the World Health
Organisation (WHO). [World Health Organisation. Global Tuberculosis Control: WHO report 2016. Geneva,
Switzerland: World Health Organisation, 2016].
The data provided suggests Lagos State has a prevalence rate of 38 out of 100 000 lives, lower than the
national average. Further information such as; stage of infection, stage of treatment, geographic location of
the patient, occupation/socio-economic status, etc., which could serve as relevant information of other risk
factors to be considered are not available.
6. Lagos State Health Scheme: Supplementary Actuarial Analysis of Tuberculosis (TB)
4 HFG, Nigeria – Abt Associates
2. Pricing and Methodology Assumptions Data
The pricing method adopted entails estimating the number of TB cases likely to be notified and treated in any particular
year over the next 3 years. This involves deriving the average number of TB cases (both DS and DR) over the past 3 years
from the service data and use this experience to project the number of cases likely to emerge in the next 3 years and then
computing the rate of utilization as the number of cases spread over the number of residents exposed (Lagos State
population). The medical cost is then determined as the product of the utilization rate and the cost of treatment.
Similarly, we have utilized the experience analysed from the historical dataset to estimate the number of tests that are
likely to be performed and projected the number of tests likely to be performed over the next 3 years. The risk premium
for testing TB is then determined as the product of the number of tests and the costs incurred in performing the test.
2.1 Encounter Data
The TB service data was provided by the LSMoH and the State’s TB co-ordination office and has been collated across all
the Local Government Areas (LGA’s) in the State. The records have been provided from years 2013 through to 2016.
The information in the dataset provided includes;
Total number of TB cases notified and further splits this into;
o Bacteriologically diagnosed cases
o Clinically diagnosed TB cases
o Cases with known HIV status
o HIV positive cases, etc.
The data can be further broken down into gender and age cohorts. In our analysis, we have utilized the age cohort to
separately determine the medical costs for drug susceptible variant of the ailment for both children (pediatrics) and
adults.
Table 2: Summary of number of DS –TB encounters from year 2013 to 2016
Age Band 2013 2014 2015 2016 2017 2018 2019
0 -14 641 636 530 509 848 1,188 1,697
15-19 629 595 623 717 1,041 1,457 2,081
20-24 910 784 792 718 1,327 1,858 2,655
25-49 5,212 5,001 4,814 4,781 7,915 11,080 15,829
50+ 1,444 1,387 1,446 1,469 2,475 3,466 4,951
Total 8,836 8,403 8,205 8,193 13,606 19,049 27,212
Projected Years
7. Lagos State Health Scheme: Supplementary Actuarial Analysis of Tuberculosis (TB)
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Table 3: Summary of number of DR –TB encounters from year 2013 to 2016
Table 4.1: Summary of TB cases in 2016
Graph 1: presentation of 2016 encounter distribution by patient category
2.2 Projected Costs
We have used the costing information provided by the National and Lagos State TB officers for cost per patient per
Age Band 2013 2014 2015 2016 2017 2018 2019
0 -14 44 44 36 35 58 82 117
15-19 43 41 43 49 72 100 143
20-24 63 54 55 49 91 128 183
25-49 359 344 331 329 545 763 1,090
50+ 99 96 100 101 170 239 341
Total 608 579 565 564 937 1,312 1,874
Projected Years
Patient Category 2016
Bacteriologically diagnosed PTB cases 6,415
Clinically diagnosed PTB Cases 2,326
Known HIV Status 8,516
TB Cases managed by TS 5,633
HIV positive TB Cases 1,440
Total TB notified 8,757
8. Lagos State Health Scheme: Supplementary Actuarial Analysis of Tuberculosis (TB)
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regimen for the drugs utilized in Lagos State. The costs have been supplied for drug susceptible treatment for adults,
drug susceptible treatment for kids (paediatrics), as well as the costs for drug resistant treatment.
2.3 Assumptions
The unit costs provided in the reference data are denominated in US dollars - we have assumed the medical cost
inflation to be 6.5% in the future projection years (PwC’s Health Research Institute – Medical cost trend in 2017).
In the base calculations, we have adopted the Central Bank of Nigeria dollar to naira exchange rate of $1:N306 at the
time of preparing this report.
We have assumed a pediatric age band to be 0 – 14 years of age
To arrive at the number of TB cases notified and under treatment in the future projection years, we have assumed the
proxy experience of 2017 will continue over the next 3 years. On average, we do not expect the impact of variable
decreases, including successful treatments and the rate of new incidences, to materially alter the average experience
going into the future.
The WHO in its 2016 report [World Health Organisation. Global Tuberculosis Control: WHO report 2016 Geneva,
Switzerland: World Health Organisation, 2016] indicated that only 15% of the total burden of the disease had been
notified in 2015. We are assuming the LSHS will intensify its efforts to capture all infected people and the roll-out of an
insurance scheme will also create a strong awareness that will enable more infected people to be captured hence, we
have assumed 25%, 35%, and 50% of the total burden of the disease will be notified in the projection years 2017, 2018
and 2019
Further assumptions in respect of utilization rates, cost of drugs and testing and the data sources are detailed in the
table below;
Table 5: The input assumptions adopted in the model
Modular pricing of TB cover Category Assumption on Utilisation
Assumtion
on Average
Unit Cost
Unit Cost in
Naira
Sources of Data
GeneXpert Test All 0.028388 11$ 3,600
Sputum Tests
Test I All 0.006231 1,500
Test II All 0.006231 1,500
Test III All 0.006231 1,500
Regimen I - Drug Susceptible TB Cases Kids - Pediatrics 0.001673 21$ 7,200
Regimen II - Drug Susceptible TB Cases Others 0.012042 21$ 7,200
Regimen III - Drug Resistant TB Cases All 0.000598 1,512$ 510,480
LagosState
M
inistry
ofHealth/TB
Coordination
Office
9. Lagos State Health Scheme: Supplementary Actuarial Analysis of Tuberculosis (TB)
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3. Results
Theresultsfromtheanalysisperformedfortheseparatemodules as wellastheoverallcost are presentedinthe following
tables. These results are on the basis that only 10% of the entire State population will take up the insurance policy;
Table 6: Modular pricing for Testing TB
The 1st General Test was computed assuming that a GeneXpert test will be performed. Subsequent tests at the end of
months 2, 4 and 6 have been estimated assuming the use of the Sputum test.
Table 7: Modular pricing for DS-TB Cases
The DS-TB cases for pediatrics have been estimated based on the assumption of children are defined as being in the age
band 0 – 14 years.
Table 8: Modular pricing for DR-TB Cases
This pricing encompasses all individuals tested, and progressed from the DS state to the DR state, and it is regarded in
this report as the 3rd Regimen.
Breakdown of TB Tests modular cost Projected amount in Naira
GeneXpert Test 92.64
Sputum Test I 9.97
Sputum Test II 9.97
Sputum Test III 9.97
Total Cost for the tests 122.54
Breakdown of DSTB modular cost Category Projected amount in Naira
Regimen I - Drug Susceptible TB Cases Kids - Pediatrics 10.92
Regimen II - Drug Susceptible TB Cases Others 78.59
Total Cost for the tests 89.51
Breakdown of DRTB modular cost Category Projected amount in Naira
Regimen III - Drug Resistant TB Cases All 276.74
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3.1 Medical Cost for additional tuberculosis (TB) cover
The overall total additional cost to the scheme is N488.79 per year, illustrated in the breakdown of costs below;
Table 9: Additional risk premium for TB cover
As mentioned in section 2, the key drivers of the above estimated costs are examined in a sensitivity analysis in Section
4.
Additional Risk premium for TB cover Projected amount in Naira
GeneXpert Test 92.64
Sputum Test I 9.97
Sputum Test II 9.97
Sputum Test III 9.97
Regimen I - DSTB for (Kids - Pediatrics) 10.92
Regimen II - DSTB for others 78.59
Regimen III - DRTB for All 276.74
Total Cost for additional TB Cover 488.79
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4. Sensitivity Analysis
In this report, we have examined changes in assumptions of the risk factors used in the actuarial analysis such as the
medical inflation rate, exchange rate, utilisation of TB services and the incidence rate. However, socio-economic risk
factors such as orientation on TB, occupation, geographical location, etc were not examined.
Table 10: Risk factors and impact on premium
A 22% increase in the cost of treatments/drugs or exchange rate of N360:$1 instead of the assumed N306:$1 will lead
to an increase in the risk premium by about 16%.
Table 11: Additional risk premium for TB assuming a medical inflation of 22%
Risk factor Shock
Impact on additional
risk premium for TB
cover
Medical Inflation 22.0% 15.9%
Exchange Rate N360: $1 instead N306:$1 16.0%
Additional Risk premium for TB cover Projected amount in Naira
GeneXpert Test 107.38
Sputum Test I 11.55
Sputum Test II 11.55
Sputum Test III 11.55
Regimen I - DSTB for (Kids - Pediatrics) 12.65
Regimen II - DSTB for others 91.10
Regimen III - DRTB for All 320.79
Total Cost for additional TB Cover 566.58
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5. Further Sensitivity and Scenario Analysis
We have considered the impact on the medical cost assuming the take-up rate of the scheme is 20% or 50% of the
entire population of the State.
Table 12: Additional risk premium for TB assuming 20% 0f Lagos populace is enrolled
This result indicates that if 20% of Lagos populace is enrolled in this scheme, there’s about a 50% drop in the risk
premium calculated.
Table 13: Additional risk premium for TB assuming 50% 0f Lagos populace is enrolled
This result also indicates 80% drop in the risk premium calculated assuming 50% of State population are enrolled on
the scheme.
Additional Risk premium for TB cover Projected amount in Naira
GeneXpert Test 46.34
Sputum Test I 4.99
Sputum Test II 4.99
Sputum Test III 4.99
Regimen I - DSTB for (Kids - Pediatrics) 5.46
Regimen II - DSTB for others 39.32
Regimen III - DRTB for All 138.43
Total Cost for additional TB Cover 244.51
Additional Risk premium for TB cover Projected amount in Naira
GeneXpert Test 18.54
Sputum Test I 1.99
Sputum Test II 1.99
Sputum Test III 1.99
Regimen I - DSTB for (Kids - Pediatrics) 2.18
Regimen II - DSTB for others 15.73
Regimen III - DRTB for All 55.39
Total Cost for additional TB Cover 97.83
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6. Conclusions
6.1 We have estimated in this supplementary analysis that an additional risk premium of N488.79 is sufficient to cover the
additional costs as the scheme kicks off. We strongly recommend that a review of this exercise is conducted a year
after the scheme kicks off and some actual experience data has been gathered.
6.2 On behalf of Ernst & Young, we thank you for the opportunity to conduct this exercise, and we look forward to
partnering with you on other similar engagements.
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7. Appendix
Table 14: Encounter data for Testing
Graph 3 – Growth curve for the projected Testing
Table 15: Costing for the Testing & three Regimens TB cases
Test Category 2016 2017 2018 2019 Average
GeneXpert Test 26,683 44,472 62,260 88,943 65,225
Sputum Test 5,857 9,762 13,666 19,523 14,317
Modular pricing
of TB cover
Category Utilisation Rate
Assumed
Average Unit
Cost
Assumed
Average Unit
Cost in Naira
GeneXpert Test All 0.0284 10.66$ 3,263.21
Sputum Tests
Test I Confirmed positive only 0.0062 5.23$ 1,599.61
Test II Confirmed positive only 0.0062 5.23$ 1,599.61
Test III Confirmed positive only 0.0062 5.23$ 1,599.61
Regimen I Drug Susceptible Pediatrics TB cases 0.0017 21.33$ 6,526.42
Regimen II Drug Susceptible Others TB cases 0.0120 21.33$ 6,526.42
Regimen III Drug Resistant TB Cases 0.0006 1,512.17$ 462,723.11
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Graph 4 – Average encounter by gender
Graph 5 – Distribution of Drug Susceptible TB cases
Graph 6 – Distribution of Drug Resistant TB cases