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Prioritization of risk groups for influenza vaccination in resource limited settings - A case study from South Africa.

ABSTRACT: BACKGROUND:Due to competing health priorities, low- and middle-income countries (LMIC) may need to prioritize between different influenza vaccine risk groups. Risk group prioritization may differ in LMIC based upon programmatic feasibility, country-specific prevalence of risk conditions and influenza-associated morbidity and mortality. METHODS:In South Africa, we collected local disease burden data (both published and unpublished) and published vaccine efficacy data in risk groups and healthy adults. We used these data to aid policy makers with risk group prioritization for influenza vaccination. We used the following formula to assess potential vaccine averted disease in each risk group: rate of influenza-associated hospitalization (or death) per 100,000 population * influenza vaccine efficacy (VE). We further estimated the cost per hospital day averted and the cost per year of life saved by influenza vaccination. RESULTS:Pregnant women, HIV-infected adults, and adults and children with tuberculosis disease had among the highest estimates of hospitalizations averted per 100,000 vaccinated and adults aged 65?years and older had the highest estimated deaths averted per 100,000 vaccinated. However, when assessing both the cost per hospital day averted (range: USD148-1,344) and the cost per year of life saved (range: USD112-1,230); adults and children with TB disease, HIV-infected adults and pregnant women had the lowest cost per outcome averted. DISCUSSION:An assessment of the potential disease outcomes averted and associated costs may aid policymakers in risk group prioritization for influenza vaccination.

SUBMITTER: McMorrow ML

PROVIDER: S-EPMC6470296 | biostudies-literature | 2019 Jan

REPOSITORIES: biostudies-literature

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Prioritization of risk groups for influenza vaccination in resource limited settings - A case study from South Africa.

McMorrow Meredith L ML Tempia Stefano S Walaza Sibongile S Treurnicht Florette K FK Ramkrishna Wayne W Azziz-Baumgartner Eduardo E Madhi Shabir A SA Cohen Cheryl C

Vaccine 20181122 1

<h4>Background</h4>Due to competing health priorities, low- and middle-income countries (LMIC) may need to prioritize between different influenza vaccine risk groups. Risk group prioritization may differ in LMIC based upon programmatic feasibility, country-specific prevalence of risk conditions and influenza-associated morbidity and mortality.<h4>Methods</h4>In South Africa, we collected local disease burden data (both published and unpublished) and published vaccine efficacy data in risk groups ...[more]

PMID: 30471956

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Project description:BackgroundCurrent critical care prognostic models are predominantly developed in high-income countries (HICs) and may not be feasible in intensive care units (ICUs) in lower- and middle-income countries (LMICs). Existing prognostic models cannot be applied without validation in LMICs as the different disease profiles, resource availability, and heterogeneity of the population may limit the transferability of such scores. A major shortcoming in using such models in LMICs is the unavailability of required measurements. This study proposes a simplified critical care prognostic model for use at the time of ICU admission.MethodsThis was a prospective study of 3855 patients admitted to 21 ICUs from Bangladesh, India, Nepal, and Sri Lanka who were aged 16 years and over and followed to ICU discharge. Variables captured included patient age, admission characteristics, clinical assessments, laboratory investigations, and treatment measures. Multivariate logistic regression was used to develop three models for ICU mortality prediction: model 1 with clinical, laboratory, and treatment variables; model 2 with clinical and laboratory variables; and model 3, a purely clinical model. Internal validation based on bootstrapping (1000 samples) was used to calculate discrimination (area under the receiver operating characteristic curve (AUC)) and calibration (Hosmer-Lemeshow C-Statistic; higher values indicate poorer calibration). Comparison was made with the Acute Physiology and Chronic Health Evaluation (APACHE) II and Simplified Acute Physiology Score (SAPS) II models.ResultsModel 1 recorded the respiratory rate, systolic blood pressure, Glasgow Coma Scale (GCS), blood urea, haemoglobin, mechanical ventilation, and vasopressor use on ICU admission. Model 2, named TropICS (Tropical Intensive Care Score), included emergency surgery, respiratory rate, systolic blood pressure, GCS, blood urea, and haemoglobin. Model 3 included respiratory rate, emergency surgery, and GCS. AUC was 0.818 (95% confidence interval (CI) 0.800-0.835) for model 1, 0.767 (0.741-0.792) for TropICS, and 0.725 (0.688-0.762) for model 3. The Hosmer-Lemeshow C-Statistic p values were less than 0.05 for models 1 and 3 and 0.18 for TropICS. In comparison, when APACHE II and SAPS II were applied to the same dataset, AUC was 0.707 (0.688-0.726) and 0.714 (0.695-0.732) and the C-Statistic was 124.84 (p < 0.001) and 1692.14 (p < 0.001), respectively.ConclusionThis paper proposes TropICS as the first multinational critical care prognostic model developed in a non-HIC setting.

Project description:Few low and middle-income countries (LMIC) have fully operational pharmacovigilance structures, systems and legal framework to collect and collate safety data and evaluate the risks and benefits by active and passive approaches. However, in a LMIC such as Sierra Leone, the capacity to manage the risks by taking appropriate preventative actions to help inform therapeutic decisions, promote rational use of medicines, guide risk management and communications is gradually growing but yet to be fully optimized. This study sought to assess the current status of pharmacovigilance in Sierra Leone since it became the 87th member of the World Health Organisation International Drug Monitoring Programme. This study evaluated the pharmacovigilance system in Sierra Leone through a comprehensive and system-based approach that covered the national medicines regulatory authority, health facilities and public health programmes. A descriptive cross-sectional study design was employed. Using a convenience sampling method, 14 respondents from the national medicines regulatory authority, six health facilities and six public health programmes were interviewed. Data were collected using a validated metric instrument: Indicator-Based Pharmacovigilance Assessment Tool. A scoring system was used for the quantification of assessment results with a score greater than 60% indicating that an organization has structural and policy frameworks to collect and collate safety data in a national database and evaluate the risks and benefits by both active and passive approaches. The study findings showed that the national medicines regulatory authority scored 79% and thus met the standard requirements of pharmacovigilance. On the other hand, the health facilities and public health programmes scored less than 60% indicating the need to fully operationalise pharmacovigilance frameworks at these levels. The study further demonstrated that the national medicine regulatory authority which hosts the national pharmacovigilance centre had functional pharmacovigilance structures and processes with potential to providing leadership in the implementation of pharmacovigilance in Sierra Leone.

Project description:The vaccines are considered to be important for the prevention and control of coronavirus disease 2019 (COVID-19). However, considering the limited vaccine supply within an extended period of time in many countries where COVID-19 vaccine booster shot are taken and new vaccines are developed to suppress the mutation of virus, designing an effective vaccination strategy is extremely important to reduce the number of deaths and infections. Then, the simulations were implemented to study the relative reduction in morbidity and mortality of vaccine allocation strategies by using the proposed model and actual South Africa's epidemiological data. Our results indicated that in light of South Africa's demographics, vaccinating older age groups (>60 years) largely reduced the cumulative deaths and the "0-20 first" strategy was the most effective way to reduce confirmed cases. In addition, "21-30 first" and "31-40 first" strategies have also had a positive effect. Partial vaccination resulted in lower numbers of infections and deaths under different control measures compared with full vaccination in low-income countries. In addition, we analyzed the sensitivity of daily testing volume and infection rate, which are critical to optimize vaccine allocation. However, comprehensive reduction in infections was mainly affected by the vaccine proportion of the target age group. An increase in the proportion of vaccines given priority to "0-20" groups always had a favorable effect, and the prioritizing vaccine allocation among the "60+" age group with 60% of the total amount of vaccine consistently resulted in the greatest reduction in deaths. Meanwhile, we observed a significant distinction in the effect of COVID-19 vaccine allocation policies under varying priority strategies on relative reductions in the effective reproduction number. Our results could help evaluate to control measures performance and the improvement of vaccine allocation strategy for COVID-19 epidemic.

Project description:ObjectiveImplementing national-level vaccination programs involves long-term investment, which can be a significant financial burden, particularly in resource-limited settings. Although many studies have assessed the economic impacts of providing vaccinations, evidence on the positive and negative implications of human resources for health (HRH) is still lacking. Therefore, this study aims to estimate the HRH impact of introducing pneumococcal conjugate vaccine (PCV) using a model-based economic evaluation.MethodsThis study adapted a Markov model from a prior study that was conducted in the Philippines for assessing the cost-effectiveness of 10-valent and 13-valent PCV compared to no vaccination. The Markov model was used for estimating the number of cases of pneumococcal-related diseases, categorized by policy options. HRH-related parameters were obtained from document reviews and interviews using the quantity, task, and productivity model (QTP model).ResultsThe number of full-time equivalent (FTE) of general practitioners, nurses, and midwives increases significantly if the universal vaccine coverage policy is implemented. A universal coverage of PCV13 - which is considered to be the best value for money compared to other vaccination strategies - requires an additional 380 FTEs for general practitioners, 602 FTEs for nurses, and 205 FTEs for midwives; it can reduce the number of FTEs for medical social workers, paediatricians, infectious disease specialists, neurologists, anaesthesiologists, radiologists, ultrasonologists, medical technologists, radiologic technologists, and pharmacists by 7, 17.9, 9.7, 0.4, 0.1, 0.7, 0.1, 12.3, 2, and 9.7, respectively, when compared to the no vaccination policy.ConclusionThis is the first attempt to estimate the impact of HRH alongside a model-based economic evaluation study, which can be eventually applied to other vaccine studies, especially those which inform resource allocation in developing settings where not only financial resources but also HRH are constrained.

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Prioritization of risk groups for influenza vaccination in resource limited settings - A case study from South Africa.

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Prioritization of risk groups for influenza vaccination in resource limited settings - A case study from South Africa.

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