Global evidence of the exposure-lag-response associations between temperature anomalies and food markets

Recent years have witnessed a landmark shift in global food prices due to the frequency of extreme weather events caused by temperature anomalies as well as the overlapping risks of COVID-19. Notably, the threat posed by temperature anomalies has spread beyond agricultural production to all aspects across food supply and demand channels, further amplifying volatility in food markets. Exploring trends in global food prices will give nations early warning signs to ensure the stability of food market. Accordingly, we utilize the Distributed Lag Non-Linear Model (DLNM) to simultaneously establish the exposure-lag-response associations between global temperature anomalies and food price returns in two dimensions: "Anomaly Degree" and "Response Time". Meanwhile, we also examine the cumulative lagged effects of temperature anomalies in terms of different quantiles and lag times. Several conclusions have been drawn. First, global food price returns will continue to decrease when the average temperature drops or rises slightly. While it turns up once the average temperature rises more than 1.1 degrees C. Second, major food commodities are more sensitive to temperature changes, and their price returns may also trend in a directional shift at different lags, with the trend in meat price being more particular. Third, food markets are more strongly affected in the case of extreme temperature anomalies. Many uncertainties still exist regarding the impact of climate change on food markets, and our work serves as a valuable reference for international trade regulation as well as the creation of dynamic climate risk hedging strategies.

Global evidence of the exposure-lag-response associations between temperature anomalies and food markets

Recent years have witnessed a landmark shift in global food prices due to the frequency of extreme weather events caused by temperature anomalies as well as the overlapping risks of COVID-19. Notably, the threat posed by temperature anomalies has spread beyond agricultural production to all aspects across food supply and demand channels, further amplifying volatility in food markets. Exploring trends in global food prices will give nations early warning signs to ensure the stability of food market. Accordingly, we utilize the Distributed Lag Non-Linear Model (DLNM) to simultaneously establish the exposure-lag-response associations between global temperature anomalies and food price returns in two dimensions: “Anomaly Degree” and “Response Time”. Meanwhile, we also examine the cumulative lagged effects of temperature anomalies in terms of different quantiles and lag times. Several conclusions have been drawn. First, global food price returns will continue to decrease when the average temperature drops or rises slightly. While it turns up once the average temperature rises more than 1.1 °C. Second, major food commodities are more sensitive to temperature changes, and their price returns may also trend in a directional shift at different lags, with the trend in meat price being more particular. Third, food markets are more strongly affected in the case of extreme temperature anomalies. Many uncertainties still exist regarding the impact of climate change on food markets, and our work serves as a valuable reference for international trade regulation as well as the creation of dynamic climate risk hedging strategies.

Seroprevalence of SARS-CoV-2 immunoglobulin antibodies in Wuhan, China: part of the city-wide massive testing campaign.

OBJECTIVES: The outbreak of the 2019 coronavirus disease (COVID-19) pandemic in Wuhan, China, has subsided after being hard hit by the disease and subsequent city lockdown. Information on the number of people involved in Wuhan is still inadequate. This study aimed to describe the screening results of 61 437 community members in Wuchang District, Wuhan. METHODS: In mid-May 2020, Wuhan launched a population-scale city-wide SARS-CoV-2 testing campaign, which aimed to perform nucleic acid and viral antibody testing for citizens in Wuhan. Here we show the screening results of cluster sampling of 61 437 residents in Wuchang District, Wuhan, China. RESULTS: A total of 1470 (2.39%, 95% CI 2.27-2.52) individuals were detected positive for at least one antiviral antibody. Among the positive individuals, 324 (0.53%, 95% CI 0.47-0.59) and 1200 (1.95%, 95% CI 1.85-2.07) were positive for immunoglobulin IgM and IgG, respectively, and 54 (0.08%, 95% CI 0.07-0.12) were positive for both antibodies. The positive rate of female carriers of antibodies was higher than those of male counterparts (male-to-female ratio of 0.75), especially in elderly citizens (ratio of 0.18 in 90+ age subgroup), indicating a sexual discrepancy in seroprevalence. In addition, viral nucleic acid detection using real-time PCR had showed 8 (0.013%, 95% CI 0.006-0.026) asymptomatic virus carriers. DISCUSSION: The seroprevalence of SARS-CoV-2 in Wuhan was low. Most Wuhan residents are still susceptible to this virus. Precautions, such as wearing mask, frequent hand hygiene and proper social distance, are necessary before an effective vaccine or antiviral treatments are available.

Clinical Characteristics and Immune Injury Mechanisms in 71 Patients with COVID-19.

The outbreak of coronavirus disease 2019 (COVID-19), caused by the novel coronavirus severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has caused a threat to global health. The mortality rate of severely ill patients in the early stage is 32.5%. The exacerbation of the condition and death of patients are closely associated with inflammatory cytokine storms, which are caused by excessive activation of the immune and complement systems as well as the coinfection of other pathogens. However, the immunological characteristics and the mechanisms underlying inflammatory storms have not been well elucidated. Here, we analyzed the clinical and immunological characteristics of 71 confirmed COVID-19 patients. Based on the National Health Commission of China (NHCC) guidelines, patients were stratified into mild and severe types. We compared the clinical and laboratory data obtained from electronic medical records between the two types. In regard to the hematological parameters, COVID-19 patients showed decreased erythrocyte count, hemoglobin, hematocrit, lymphocyte count, eosinophil count, and complement C1q, whereas neutrophils, C-reactive protein, and procalcitonin were significantly increased, especially in severe cases. We also found that CD3+ CD4+ T lymphocytes, CD3+ CD8+ T lymphocytes, CD19+ B lymphocytes, and CD16+ CD56+ NK cells in the peripheral blood of all patients were decreased. In addition, CD3+ CD8+ T lymphocytes, CD16+ CD56+ NK cells, and complement C1q in severely ill patients decreased more significantly. Additionally, interleukin 6 (IL-6) elevation was particularly prominent in all patients, especially in severe cases. These results suggest that CD3+ CD8+ T lymphocytes, CD16+ CD56+ NK cells, C1q as well as IL-6 may play critical roles in the inflammatory cytokine storm. The dysregulation of these aforementioned immune parameters, along with bacterial coinfection, were the important causes of exacerbation of the patients' condition and death. This study improves our understanding of the immune dysregulation of COVID-19 and provides potential immunotherapeutic strategies.IMPORTANCE The dysregulation of CD3+ CD8+ T lymphocytes, CD16+ CD56+ NK cells, C1q as well as IL-6, along with bacterial coinfection, were important causes of exacerbation of the patients' condition and death.

Serological immunochromatographic approach in diagnosis with SARS-CoV-2 infected COVID-19 patients.

An outbreak of new coronavirus SARS-CoV-2 was occurred in Wuhan, China and rapidly spread to other cities and nations. The standard diagnostic approach that widely adopted in the clinic is nucleic acid detection by real-time RT-PCR. However, the false-negative rate of the technique is unneglectable and serological methods are urgently warranted. Here, we presented the colloidal gold-based immunochromatographic (ICG) strip targeting viral IgM or IgG antibody and compared it with real-time RT-PCR. The sensitivity of ICG assay with IgM and IgG combinatorial detection in nucleic acid confirmed cases were 11.1%, 92.9% and 96.8% at the early stage (1-7 days after onset), intermediate stage (8-14 days after onset), and late stage (more than 15 days), respectively. The ICG detection capacity in nucleic acid-negative suspected cases was 43.6%. In addition, the concordance of whole blood samples and plasma showed Cohen's kappa value of 0.93, which represented the almost perfect agreement between two types of samples. In conclusion, serological ICG strip assay in detecting SARS-CoV-2 infection is both sensitive and consistent, which is considered as an excellent supplementary approach in clinical application.