Quantifying and monitoring the spatial and temporal dynamics of the global land cover is critical for better understanding many of the Earth’s land surface processes. However, the lack of regularly updated, continental-scale, and high spatial resolution (30 m) land cover data limit our ability to better understand the spatial extent and the temporal dynamics of land surface changes. Despite the free availability of high spatial resolution Landsat satellite data, continental-scale land cover mapping using high resolution Landsat satellite data was not feasible until now due to the need for high-performance computing to store, process, and analyze this large volume of high resolution satellite data. In this study, we present an approach to quantify continental land cover and impervious surface changes over a long period of time (15 years) using high resolution Landsat satellite observations and Google Earth Engine cloud computing platform. The approach applied here to overcome the computational challenges of handling big earth observation data by using cloud computing can help scientists and practitioners who lack high-performance computational resources.

Background: Malaria is one of the leading public health problems in most of sub-Saharan Africa, particularly in Ethiopia. Almost all demographic groups are at risk of malaria because of seasonal and unstable transmission of the disease. Therefore, there is a need to develop malaria early-warning systems to enhance public health decision making for control and prevention of malaria epidemics. Data from orbiting earth-observing sensors can monitor environmental risk factors that trigger malaria epidemics. Remotely sensed environmental indicators were used to examine the influences of climatic and environmental variability on temporal patterns of malaria cases in the Amhara region of Ethiopia. Methods: In this study seasonal autoregressive integrated moving average (SARIMA) models were used to quantify the relationship between malaria cases and remotely sensed environmental variables, including rainfall, land-surface temperature (LST), vegetation indices (NDVI and EVI), and actual evapotranspiration (ETa) with lags ranging from one to three months. Predictions from the best model with environmental variables were compared to the actual observations from the last 12 months of the time series. Results: Malaria cases exhibited positive associations with LST at a lag of one month and positive associations with indicators of moisture (rainfall, EVI and ETa) at lags from one to three months. SARIMA models that included these environmental covariates had better fits and more accurate predictions, as evidenced by lower AIC and RMSE values, than models without environmental covariates. Conclusions: Malaria risk indicators such as satellite-based rainfall estimates, LST, EVI, and ETa exhibited significant lagged associations with malaria cases in the Amhara region and improved model fit and prediction accuracy. These variables can be monitored frequently and extensively across large geographic areas using data from earth-observing sensors to support public health decisions.

The impacts of interannual climate fluctuations on vector-borne diseases, especially malaria, have received considerable attention in the scientific literature. These effects can be significant in semi-arid and high-elevation areas such as the highlands of East Africa because cooler temperature and seasonally dry conditions limit malaria transmission. Many previous studies have examined short-term lagged effects of climate on malaria (weeks to months), but fewer have explored the possibility of longer-term seasonal effects. This study assessed the interannual variability of malaria occurrence from 2001 to 2009 in the Amhara region of Ethiopia. We tested for associations of climate variables summarized during the dry (January–April), early transition (May–June), and wet (July–September) seasons with malaria incidence in the early peak (May–July) and late peak (September–December) epidemic seasons using generalized linear models. Climate variables included land surface temperature (LST), rainfall, actual evapotranspiration (ET), and the enhanced vegetation index (EVI). We found that both early and late peak malaria incidence had the strongest associations with meteorological conditions in the preceding dry and early transition seasons. Temperature had the strongest influence in the wetter western districts, whereas moisture variables had the strongest influence in the drier eastern districts. We also found a significant correlation between malaria incidence in the early and the subsquent late peak malaria seasons, and the addition of early peak malaria incidence as a predictor substantially improved models of late peak season malaria in both of the study sub-regions. These findings suggest that climatic effects on malaria prior to the main rainy season can carry over through the rainy season and affect the probability of malaria epidemics during the late malaria peak. The results also emphasize the value of combining environmental monitoring with epidemiological surveillance to develop forecasts of malaria outbreaks, as well as the need for spatially stratified approaches that reflect the differential effects of climatic variations in the different sub-regions.

Artemisinin-based combination therapies (ACTs) are the most effective treatment for uncomplicated Plasmodium falciparum malaria infection. A commonly used indicator for monitoring and assessing progress in coverage of malaria treatment is the proportion of children younger than 5 years with reported fever in the previous 14 days who have received an ACT. We propose an improved indicator that incorporates parasite infection status (as assessed by a rapid diagnostic test [RDT]), which is available in recent household surveys. In this study we estimated the annual proportion of children younger than 5 years with fever and a positive RDT in Africa who received an ACT in 2003-15. Our modelling study used cross-sectional data on treatment for fever and RDT status for children younger than 5 years compiled from all nationally available representative household surveys (the Malaria Indicator Surveys, Demographic and Health Surveys, and Multiple Indicator Cluster Surveys) across sub-Saharan Africa between 2003 and 2015. Estimates for the proportion of children younger than 5 years with a fever within the previous 14 days and P falciparum infection assessed by RDT who received an ACT were incorporated in a generalised additive mixed model, including data on ACT distributions, to estimate coverage across all countries and time periods. We did random effects meta-analyses to examine individual, household, and community effects associated with ACT coverage. We obtained data on 201 704 children younger than 5 years from 103 surveys (22 MIS, 61 DHS, and 20 MICS) across 33 countries. RDT results were available for 40 of these surveys including 40 261 (20%) children, and we predicted RDT status for the remaining 161 443 (80%) children. Our results showed that ACT coverage in children younger than 5 years with a fever and P falciparum infection increased across sub-Saharan Africa in 2003-15, but even in 2015, only 19·7% (95% CI 15·6-24·8) of children younger than 5 years with a fever and P falciparum infection received an ACT. In meta-analyses, children younger than 5 years were more likely to receive an ACT for fever and P falciparum infection if they lived in an urban area (vs rural area; odds ratio [OR] 1·18, 95% CI 1·06-1·31), had household wealth above the national median (vs wealth below the median; OR 1·26, 1·16-1·39), had a caregiver with any education (vs no education; OR 1·31, 1·22-1·41), had a household insecticide-treated net (ITN; vs no ITN; OR 1·21, 1·13-1·29), were older than 2 years (vs ≤2 years; OR 1·09, 1·01-1·17), or lived in an area with a higher mean P falciparum prevalence in children aged 2-10 years (OR 1·12, 1·02-1·23). In the subgroup of children for whom treatment was sought, those who sought treatment in the public sector were more likely to receive an ACT (vs the private sector; OR 3·18, 2·67-3·78). Despite progress during the 2003-15 malaria programme, ACT treatment for children with malaria remains unacceptably low. More work is needed at the country level to understand how health-care access, service delivery, and ACT supply might be improved to ensure appropriate treatment for all children with malaria. US President's Malaria Initiative and Medicines for Malaria Venture.

Since 2010, the Roll Back Malaria (RBM) Partnership, including National Malaria Control Programs, donor agencies (e.g., President's Malaria Initiative and Global Fund), and other stakeholders have been evaluating the impact of scaling up malaria control interventions on all-cause under-five mortality in several countries in sub-Saharan Africa. The evaluation framework assesses whether the deployed interventions have had an impact on malaria morbidity and mortality and requires consideration of potential nonintervention influencers of transmission, such as drought/floods or higher temperatures. Herein, we assess the likely effect of climate on the assessment of the impact malaria interventions in 10 priority countries/regions in eastern, western, and southern Africa for the President's Malaria Initiative. We used newly available quality controlled Enhanced National Climate Services rainfall and temperature products as well as global climate products to investigate likely impacts of climate on malaria evaluations and test the assumption that changing the baseline period can significantly impact on the influence of climate in the assessment of interventions. Based on current baseline periods used in national malaria impact assessments, we identify three countries/regions where current evaluations may overestimate the impact of interventions (Tanzania, Zanzibar, Uganda) and three countries where current malaria evaluations may underestimate the impact of interventions (Mali, Senegal and Ethiopia). In four countries (Rwanda, Malawi, Mozambique, and Angola) there was no strong difference in climate suitability for malaria in the pre- and post-intervention period. In part, this may be due to data quality and analysis issues.

In malaria elimination settings, all malaria cases must be identified, documented and investigated. To facilitate complete and timely reporting of all malaria cases and effective case management and follow-up, engagement with private providers is essential, particularly in settings where the private sector is a major source of healthcare. However, research on the role and performance of the private sector in malaria diagnosis, case management and reporting in malaria elimination settings is limited. Moreover, the most effective strategies for private sector engagement in malaria elimination settings remain unclear. Twenty-five experts in malaria elimination, disease surveillance and private sector engagement were purposively sampled and interviewed. An extensive review of grey and peer-reviewed literature on private sector testing, treatment, and reporting for malaria was performed. Additional in-depth literature review was conducted for six case studies on eliminating and neighbouring countries in Southeast Asia and Southern Africa. The private health sector can be categorized based on their commercial orientation or business model (for-profit versus nonprofit) and their regulation status within a country (formal vs informal). A number of potentially effective strategies exist for engaging the private sector. Conducting a baseline assessment of the private sector is critical to understanding its composition, size, geographical distribution and quality of services provided. Facilitating reporting, referral and training linkages between the public and private sectors and making malaria a notifiable disease are important strategies to improve private sector involvement in malaria surveillance. Financial incentives for uptake of rapid diagnostic tests and artemisinin-based combination therapy should be combined with training and community awareness campaigns for improving uptake. Private sector providers can also be organized and better engaged through social franchising, effective regulation, professional organizations and government outreach. This review highlights the importance of engaging private sector stakeholders early and often in the development of malaria elimination strategies.