Although mutations drive the evolutionary process, the rates at which the mutations occur are themselves subject to evolutionary forces. Our purpose here is to understand the role of selection and random genetic drift in the evolution of mutation rates, and we address this question in asexual populations at mutation‐selection equilibrium neglecting selective sweeps. Using a multitype branching process, we calculate the fixation probability of a rare nonmutator in a large asexual population of mutators and find that a nonmutator is more likely to fix when the deleterious mutation rate of the mutator population is high. Compensatory mutations in the mutator population are found to decrease the fixation probability of a nonmutator when the selection coefficient is large. But, surprisingly, the fixation probability changes nonmonotonically with increasing compensatory mutation rate when the selection is mild. Using these results for the fixation probability and a drift‐barrier argument, we find a novel relationship between the mutation rates and the population size. We also discuss the time to fix the nonmutator in an adapted population of asexual mutators, and compare our results with experiments.

IntroductionSince sex-based biological and gender factors influence COVID-19 mortality, we wanted to investigate the difference in mortality rates between women and men in sub-Saharan Africa (SSA).MethodWe included 69 580 cases of COVID-19, stratified by sex (men: n=43 071; women: n=26 509) and age (0–39 years: n=41 682; 40–59 years: n=20 757; 60+ years: n=7141), from 20 member nations of the WHO African region until 1 September 2020. We computed the SSA-specific and country-specific case fatality rates (CFRs) and sex-specific CFR differences across various age groups, using a Bayesian approach.ResultsA total of 1656 deaths (2.4% of total cases reported) were reported, with men accounting for 70.5% of total deaths. In SSA, women had a lower CFR than men (mean CFRdiff = −0.9%; 95% credible intervals (CIs) −1.1% to −0.6%). The mean CFR estimates increased with age, with the sex-specific CFR differences being significant among those aged 40 years or more (40–59 age group: mean CFRdiff = −0.7%; 95% CI −1.1% to −0.2%; 60+ years age group: mean CFRdiff = −3.9%; 95% CI −5.3% to −2.4%). At the country level, 7 of the 20 SSA countries reported significantly lower CFRs among women than men overall. Moreover, corresponding to the age-specific datasets, significantly lower CFRs in women than men were observed in the 60+ years age group in seven countries and 40–59 years age group in one country.ConclusionsSex and age are important predictors of COVID-19 mortality globally. Countries should prioritise the collection and use of sex-disaggregated data so as to design public health interventions and ensure that policies promote a gender-sensitive public health response.

Objective: To quantify the initial spread of COVID-19 in the WHO African region, and to investigate the possible drivers responsible for variation in the epidemic among member states. Design: A cross-sectional study. Setting: COVID-19 daily case and death data from the initial case through 29 November 2020. Participants: 46 countries comprising the WHO African region. Main outcome measures: We used five pandemic response indicators for each country: speed at which the pandemic reached the country, speed at which the first 50 cases accumulated, maximum monthly attack rate, cumulative attack rate, and crude case fatality ratio (CFR). We studied the effect of 13 predictor variables on the country-level variation in them using a principal component analysis, followed by regression. Results: Countries with higher tourism activities, GDP per capita, and proportion of older people had higher monthly (p < 0.001) and cumulative attack rates (p < 0.001) and lower CFRs (p = 0.052). Countries having more stringent early COVID-19 response policies experienced greater delay in arrival of the first case (p < 0.001). The speed at which the first 50 cases occurred was slower in countries whose neighbors had higher cumulative attack rates (p = 0.06). Conclusions: While global connectivity and tourism could facilitate the spread of airborne infectious agents, the observed differences in attack rates between African countries might also be due to differences in testing capacities or age distribution. Wealthy countries managed to minimize adverse outcomes. Further, careful and early implementation of strict government policies, such as restricting tourism, could be pivotal to controlling the COVID-19 pandemic. Evidently, good quality data and sufficient testing capacities are essential to unravel the epidemiology of an outbreak. We thus urge decision-makers to reduce these barriers to ensure rapid responses to future threats to public health and economic stability.

Transmission bottlenecks introduce selection pressures on HIV-1 that vary with the mode of transmission. Recent studies on small cohorts have suggested that stronger selection pressures lead to fitter transmitted/founder (T/F) strains. Manifestations of this selection bias at the population level have remained elusive. Here, we analysed early CD4 cell count measurements reported from ∼340,000 infected heterosexual individuals (HET) and men-who-have-sex-with-men (MSM), across geographies, ethnicities and calendar years. The reduction in CD4 counts early in infection is reflective of the virulence of T/F strains. MSM and HET use predominant modes of transmission, namely, anal and penile-vaginal, with among the largest differences in the selection pressures at transmission across modes. Further, in most geographies, the groups show little inter-mixing, allowing for the differential selection bias to be sustained and amplified. We found that the early reduction in CD4 counts was consistently greater in HET than MSM (P<0.05). To account for inherent variations in baseline CD4 counts, we constructed a metric to quantify the extent of progression to AIDS as the ratio of the reduction in measured CD4 counts from baseline and the reduction associated with AIDS. We found that this progression corresponding to the early CD4 measurements was ∼68% for MSM and ∼87% for HET on average (P<10−4; Cohen’s d, ds = 0.36), reflecting the more severe disease caused by T/F strains in HET than MSM at the population level. Interestingly, the set-point viral load was not different between the groups (ds<0.12), suggesting that MSM were more tolerant and not more resistant to their T/F strains than HET. This difference remained when we controlled for confounding factors using multivariable regression. We concluded that the different selection pressures at transmission have resulted in more virulent T/F strains in HET than MSM. These findings have implications for our understanding of HIV-1 pathogenesis, evolution, and epidemiology.

Objective: To investigate differences of COVID-19 related mortality among women and men across sub-Saharan Africa (SSA) from the beginning of the pandemic. Design: A cross sectional study. Setting: Data from 20 member nations of the WHO African region until September 1, 2020. Participants: 69,580 cases of COVID-19, stratified by sex (men, n=43071; women, n=26509) and age (0-39 years, n=41682; 40-59 years, n=20757; 60+ years, n=7141). Main outcome measures: We computed the SSA- and country-specific case fatality rates (CFRs) and sex-specific CFR differences across various age groups, using a Bayesian approach. Results: A total of 1,656 (2.4% of total cases reported; 1656/69580) deaths were reported, with men accounting for 1168/1656 (70.5%) of total deaths. In SSA, women had a lower CFR than men (mean CFR<diff> = -0.9%; 95% credible intervals -1.1% to -0.6%). The mean CFR estimates increased with age, with the sex-specific CFR differences being significant among those aged 40 or more (40-59 age-group: mean CFR<diff> = -0.7%; 95% credible intervals -1.1% to -0.2%; 60+ age-group: mean CFR<diff> = -3.9%; 95% credible intervals -5.3% to -2.4%). At the country level, seven of the twenty SSA countries reported significantly lower CFRs among women than men overall. Moreover, corresponding to the age-specific datasets, significantly lower CFRs in women than men were observed in the 60+ age-group in seven countries and 40-59 age-group in one country. Conclusions: Sex and age are important predictors of COVID-19 mortality. Countries should prioritize the collection and use of sex-disaggregated data to understand the evolution of the pandemic. This is essential to design public health interventions and ensure that policies promote a gender sensitive public health response.

During the first wave of the COVID-19 pandemic, sub-Saharan African countries experienced comparatively lower rates of SARS-CoV-2 infections and related deaths than in other parts of the world, the reasons for which remain unclear. Yet, there was also considerable variation between countries. Here, we explored potential drivers of this variation among 46 of the 47 WHO African region Member States in a cross-sectional study. We described five indicators of early COVID-19 spread and severity for each country as of 29 November 2020: delay in detection of the first case, length of the early epidemic growth period, cumulative and peak attack rates and crude case fatality ratio (CFR). We tested the influence of 13 pre-pandemic and pandemic response predictor variables on the country-level variation in the spread and severity indicators using multivariate statistics and regression analysis. We found that wealthier African countries, with larger tourism industries and older populations, had higher peak (p<0.001) and cumulative (p<0.001) attack rates, and lower CFRs (p=0.021). More urbanised countries also had higher attack rates (p<0.001 for both indicators). Countries applying more stringent early control policies experienced greater delay in detection of the first case (p<0.001), but the initial propagation of the virus was slower in relatively wealthy, touristic African countries (p=0.023). Careful and early implementation of strict government policies were likely pivotal to delaying the initial phase of the pandemic, but did not have much impact on other indicators of spread and severity. An over-reliance on disruptive containment measures in more resource-limited contexts is neither effective nor sustainable. We thus urge decision-makers to prioritise the reduction of resource-based health disparities, and surveillance and response capacities in particular, to ensure global resilience against future threats to public health and economic stability.

In an adapted population of mutators in which most mutations are deleterious, a nonmutator that lowers the mutation rate is under indirect selection and can sweep to fixation. Using a multitype branching process, we calculate the fixation probability of a rare nonmutator in a large population of asexual mutators. We show that when beneficial mutations are absent, the fixation probability is a nonmonotonic function of the mutation rate of the mutator: it first increases sublinearly and then decreases exponentially. We also find that beneficial mutations can enhance the fixation probability of a nonmutator. Our analysis is relevant to an understanding of recent experiments in which a reduction in the mutation rates has been observed.

The geographic and economic characteristics unique to island nations create a different set of conditions for, and responses to, the spread of a pandemic compared with those of mainland countries. Here, we aimed to describe the initial period of the COVID-19 pandemic, along with the potential conditions and responses affecting variation in the burden of infections and severe disease burden, across the six island nations of the WHO’s Africa region: Cabo Verde, Comoros, Madagascar, Mauritius, São Tomé e Príncipe and Seychelles. We analysed the publicly available COVID-19 data on confirmed cases and deaths from the beginning of the pandemic through 29 November 2020. To understand variation in the course of the pandemic in these nations, we explored differences in their economic statuses, healthcare expenditures and facilities, age and sex distributions, leading health risk factors, densities of the overall and urban populations and the main industries in these countries. We also reviewed the non-pharmaceutical response measures implemented nationally. We found that the burden of SARS-CoV-2 infection was reduced by strict early limitations on movement and biased towards nations where detection capacity was higher, while the burden of severe COVID-19 was skewed towards countries that invested less in healthcare and those that had older populations and greater prevalence of key underlying health risk factors. These findings highlight the need for Africa’s island nations to invest more in healthcare and in local testing capacity to reduce the need for reliance on border closures that have dire consequences for their economies.