Policy decisions on COVID-19 interventions should be informed by a local, regional and national understanding of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission. Epidemic waves may result when restrictions are lifted or poorly adhered to, variants with new phenotypic properties successfully invade, or infection spreads to susceptible subpopulations. Three COVID-19 epidemic waves have been observed in Kenya. Using a mechanistic mathematical model, we explain the first two distinct waves by differences in contact rates in high and low social-economic groups, and the third wave by the introduction of higher-transmissibility variants. Reopening schools led to a minor increase in transmission between the second and third waves. Socioeconomic and urban-rural population structure are critical determinants of viral transmission in Kenya.

Policy makers in Africa need robust estimates of the current and future spread of SARS-CoV-2. Data suitable for this purpose are scant. We used national surveillance PCR test, serological survey and mobility data to develop and fit a county-specific transmission model for Kenya. We estimate that the SARS-CoV-2 pandemic peaked before the end of July 2020 in the major urban counties, with 34 - 41% of residents infected, and will peak elsewhere in the country within 2-3 months. Despite this penetration, reported severe cases and deaths are low. Our analysis suggests the COVID-19 disease burden in Kenya may be far less than initially feared. A similar scenario across sub-Saharan Africa would have implications for balancing the consequences of restrictions with those of COVID-19.

Background The COVID-19 pandemic has disrupted routine measles immunisation and supplementary immunisation activities (SIAs) in most countries including Kenya. We assessed the risk of measles outbreaks during the pandemic in Kenya as a case study for the African Region. Methods Combining measles serological data, local contact patterns, and vaccination coverage into a cohort model, we predicted the age-adjusted population immunity in Kenya and estimated the probability of outbreaks when contact-reducing COVID-19 interventions are lifted. We considered various scenarios for reduced measles vaccination coverage from April 2020. Results In February 2020, when a scheduled SIA was postponed, population immunity was close to the herd immunity threshold and the probability of a large outbreak was 34% (8–54). As the COVID-19 contact restrictions are nearly fully eased, from December 2020, the probability of a large measles outbreak will increase to 38% (19–54), 46% (30–59), and 54% (43–64) assuming a 15%, 50%, and 100% reduction in measles vaccination coverage. By December 2021, this risk increases further to 43% (25–56), 54% (43–63), and 67% (59–72) for the same coverage scenarios respectively. However, the increased risk of a measles outbreak following the lifting of all restrictions can be overcome by conducting a SIA with ≥ 95% coverage in under-fives. Conclusion While contact restrictions sufficient for SAR-CoV-2 control temporarily reduce measles transmissibility and the risk of an outbreak from a measles immunity gap, this risk rises rapidly once these restrictions are lifted. Implementing delayed SIAs will be critical for prevention of measles outbreaks given the roll-back of contact restrictions in Kenya.

Background Studies of the African savannas have used national parks to test ecological theories of natural ecosystems, including equilibrium, non-equilibrium, complex adaptive systems, and the role of top-down and bottom-up physical and biotic forces. Most such studies have excluded the impact of pastoralists in shaping grassland ecosystems and, over the last half century, the growing human impact on the world’s rangelands. The mounting human impact calls for selecting indicators and integrated monitoring methods able to track ecosystem changes and the role of natural and human agencies. Our study draws on five decades of monitoring the Amboseli landscape in southern Kenya to document the declining role of natural agencies in shaping plant ecology with rising human impact. Results We show that plant diversity and productivity have declined, biomass turnover has increased in response to a downsizing of mean plant size, and that ecological resilience has declined with the rising probability of extreme shortfalls in pasture production. The signature of rainfall and physical agencies in driving ecosystem properties has decreased sharply with growing human impact. We compare the Amboseli findings to the long-term studies of Kruger and Serengeti national parks to show that the human influence, whether by design or default, is increasingly shaping the ecology of savanna ecosystems. We look at the findings in the larger perspective of human impact on African grasslands and the world rangelands, in general, and discuss the implications for ecosystem theory and conservation policy and management. Conclusions The Amboseli study shows the value of using long-term integrated ecological monitoring to track the spatial and temporal changes in the species composition, structure, and function of rangeland ecosystems and the role of natural and human agencies in the process of change. The study echoes the widespread changes underway across African savannas and world’s rangelands, concluding that some level of ecosystem management is needed to prevent land degradation and the erosion of ecological function, services, and resilience. Despite the weak application of ecological theory to conservation management, a plant trait-based approach is shown to be useful in explaining the macroecological changes underway.