Towards the development of a SARS-CoV-2 variant risk assessment tool: expert consultation on the assessment of scientific evidence on emerging variants.

A systematic approach is required for the development of an evidence-based risk assessment tool to robustly estimate the risks and implications of SARS-CoV-2 variants. We conducted a survey among experts involved in technical advisory roles for WHO to capture their assessment of the robustness of different study types that provide evidence for potential changes in transmissibility, antigenicity, virulence, treatability, and detectability of SARS-CoV-2 variants. The views of 62 experts indicated that studies could be grouped on the basis of robustness and reliability for the different risk indicators mentioned. Several study types that experts scored as providing reliable evidence and that can be performed in a timely manner were identified. Although experts from different technical areas had varying responses, there was agreement on the highest and lowest scoring study types. These findings can help to prioritise, harmonise, and optimise study designs for the further development of a systematic, evidence-based, SARS-CoV-2 variant risk assessment tool.

Yellow Fever in Africa: estimating the burden of disease and impact of mass vaccination from outbreak and serological data.

BACKGROUND: Yellow fever is a vector-borne disease affecting humans and non-human primates in tropical areas of Africa and South America. While eradication is not feasible due to the wildlife reservoir, large scale vaccination activities in Africa during the 1940s to 1960s reduced yellow fever incidence for several decades. However, after a period of low vaccination coverage, yellow fever has resurged in the continent. Since 2006 there has been substantial funding for large preventive mass vaccination campaigns in the most affected countries in Africa to curb the rising burden of disease and control future outbreaks. Contemporary estimates of the yellow fever disease burden are lacking, and the present study aimed to update the previous estimates on the basis of more recent yellow fever occurrence data and improved estimation methods. METHODS AND FINDINGS: Generalised linear regression models were fitted to a dataset of the locations of yellow fever outbreaks within the last 25 years to estimate the probability of outbreak reports across the endemic zone. Environmental variables and indicators for the surveillance quality in the affected countries were used as covariates. By comparing probabilities of outbreak reports estimated in the regression with the force of infection estimated for a limited set of locations for which serological surveys were available, the detection probability per case and the force of infection were estimated across the endemic zone. The yellow fever burden in Africa was estimated for the year 2013 as 130,000 (95% CI 51,000-380,000) cases with fever and jaundice or haemorrhage including 78,000 (95% CI 19,000-180,000) deaths, taking into account the current level of vaccination coverage. The impact of the recent mass vaccination campaigns was assessed by evaluating the difference between the estimates obtained for the current vaccination coverage and for a hypothetical scenario excluding these vaccination campaigns. Vaccination campaigns were estimated to have reduced the number of cases and deaths by 27% (95% CI 22%-31%) across the region, achieving up to an 82% reduction in countries targeted by these campaigns. A limitation of our study is the high level of uncertainty in our estimates arising from the sparseness of data available from both surveillance and serological surveys. CONCLUSIONS: With the estimation method presented here, spatial estimates of transmission intensity can be combined with vaccination coverage levels to evaluate the impact of past or proposed vaccination campaigns, thereby helping to allocate resources efficiently for yellow fever control. This method has been used by the Global Alliance for Vaccines and Immunization (GAVI Alliance) to estimate the potential impact of future vaccination campaigns.

Epidemiologic and virologic assessment of the 2009 influenza A (H1N1) pandemic on selected temperate countries in the Southern Hemisphere: Argentina, Australia, Chile, New Zealand and South Africa.

UNLABELLED: INTRODUCTION AND SETTING: Our analysis compares the most comprehensive epidemiologic and virologic surveillance data compiled to date for laboratory-confirmed H1N1pdm patients between 1 April 2009 - 31 January 2010 from five temperate countries in the Southern Hemisphere-Argentina, Australia, Chile, New Zealand, and South Africa. OBJECTIVE: We evaluate transmission dynamics, indicators of severity, and describe the co-circulation of H1N1pdm with seasonal influenza viruses. RESULTS: In the five countries, H1N1pdm became the predominant influenza strain within weeks of initial detection. South Africa was unique, first experiencing a seasonal H3N2 wave, followed by a distinct H1N1pdm wave. Compared with the 2007 and 2008 influenza seasons, the peak of influenza-like illness (ILI) activity in four of the five countries was 3-6 times higher with peak ILI consultation rates ranging from 35/1,000 consultations/week in Australia to 275/100,000 population/week in New Zealand. Transmission was similar in all countries with the reproductive rate ranging from 1.2-1.6. The median age of patients in all countries increased with increasing severity of disease, 4-14% of all hospitalized cases required critical care, and 26-68% of fatal patients were reported to have ≥1 chronic medical condition. Compared with seasonal influenza, there was a notable downward shift in age among severe cases with the highest population-based hospitalization rates among children <5 years old. National population-based mortality rates ranged from 0.8-1.5/100,000. CONCLUSIONS: The difficulty experienced in tracking the progress of the pandemic globally, estimating its severity early on, and comparing information across countries argues for improved routine surveillance and standardization of investigative approaches and data reporting methods.