Dynamic variations in COVID-19 with the SARS-CoV-2 Omicron variant in Kazakhstan and Pakistan.

BACKGROUND: The ongoing coronavirus disease 2019 (COVID-19) pandemic caused by the severe acute respiratory syndrome-coronavirus 2 (SARS-CoV-2) and the Omicron variant presents a formidable challenge for control and prevention worldwide, especially for low- and middle-income countries (LMICs). Hence, taking Kazakhstan and Pakistan as examples, this study aims to explore COVID-19 transmission with the Omicron variant at different contact, quarantine and test rates. METHODS: A disease dynamic model was applied, the population was segmented, and three time stages for Omicron transmission were established: the initial outbreak, a period of stabilization, and a second outbreak. The impact of population contact, quarantine and testing on the disease are analyzed in five scenarios to analysis their impacts on the disease. Four statistical metrics are employed to quantify the model's performance, including the correlation coefficient (CC), normalized absolute error, normalized root mean square error and distance between indices of simulation and observation (DISO). RESULTS: Our model has high performance in simulating COVID-19 transmission in Kazakhstan and Pakistan with high CC values greater than 0.9 and DISO values less than 0.5. Compared with the present measures (baseline), decreasing (increasing) the contact rates or increasing (decreasing) the quarantined rates can reduce (increase) the peak values of daily new cases and forward (delay) the peak value times (decreasing 842 and forward 2 days for Kazakhstan). The impact of the test rates on the disease are weak. When the start time of stage II is 6 days, the daily new cases are more than 8 and 5 times the rate for Kazakhstan and Pakistan, respectively (29,573 vs. 3259; 7398 vs. 1108). The impact of the start times of stage III on the disease are contradictory to those of stage II. CONCLUSIONS: For the two LMICs, Kazakhstan and Pakistan, stronger control and prevention measures can be more effective in combating COVID-19. Therefore, to reduce Omicron transmission, strict management of population movement should be employed. Moreover, the timely application of these strategies also plays a key role in disease control.

Spatiotemporal changes, trade-offs, and synergistic relationships in ecosystem services provided by the Aral Sea Basin.

Intense human activities in the Aral Sea Basin have changed its natural distribution of land use. Although they provide certain economic benefits, these anthropogenic influences have led to the rapid shrinkage of the Aral Sea, severely affecting the region's ecosystem. However, the spatiotemporal variability of the Aral Sea Basin's Ecosystem Service Values (ESVs) is not well understood. In this study, we used 300-meter resolution land use maps from 1995, 2005, and 2015 and the Patch-generating Land Use Simulation (PLUS) model to predict the future land use patterns of the Aral Sea Basin in 2025. Simultaneously, we divided the Aral Sea Basin into three regions (upstream, midstream, and downstream) and evaluated the dynamic responses of their ESVs to Land Use and Land Cover (LULC) changes. The changes in the types of ecosystem services provided by the Aral Sea Basin, their trade-off, and synergistic relationships were analyzed by weighting their associations. The results showed that from 1995 to 2025, the grassland, urban, and cropland areas in the Aral Sea Basin will expand rapidly, while the areas covered by water bodies will shrink rapidly, causing a total loss of 31.97 billion USD. The downstream loss of 27.79 billion USD of the total amount is mainly caused by the conversion of water bodies to bare land. The ESVs of the middle region will increase by 6.81 billion USD, mainly due to the large amount of water extracted from the Amu Darya and Syr Darya Rivers in the middle regions of the Aral Sea Basin that are used to reclaim cultivated land and expand urban areas. The ESVs and areas experiencing land use changes in the upper regions are relatively small. At the same time, our results show that biodiversity, food production, and water regulation are the major ecosystem service functions, and account for 79.46% of the total ESVs. Of the ecosystem service relationships in the Aral Sea Basin, synergy accounts for 55.56% of the interactions, with a fewer amount of trade-off exchanges. This synergy mainly exists in the relationships involving water regulation, waste treatment and recreation, and culture and tourism. We propose protection measures that will coordinate eco-environmental protection efforts with socioeconomic development in the region in order to achieve the United Nations' sustainable development goals.