Malaria predictions based on seasonal climate forecasts in South Africa: A time series distributed lag nonlinear model

Although there have been enormous demands and efforts to develop an early warning system for malaria, no sustainable system has remained. Well-organized malaria surveillance and high-quality climate forecasts are required to sustain a malaria early warning system in conjunction with an effective malaria prediction model. We aimed to develop a weather-based malaria prediction model using a weekly time-series data including temperature, precipitation, and malaria cases from 1998 to 2015 in Vhembe, Limpopo, South Africa and apply it to seasonal climate forecasts. The malaria prediction model performed well for short-term predictions (correlation coefficient, r?>?0.8 for 1- and 2-week ahead forecasts). The prediction accuracy decreased as the lead time increased but retained fairly good performance (r?>?0.7) up to the 16-week ahead prediction. The demonstration of the malaria prediction process based on the seasonal climate forecasts showed the short-term predictions coincided closely with the observed malaria cases. The weather-based malaria prediction model we developed could be applicable in practice together with skillful seasonal climate forecasts and existing malaria surveillance data. Establishing an automated operating system based on real-time data inputs will be beneficial for the malaria early warning system, and can be an instructive example for other malaria-endemic areas.Publisher Correction: A supplementary file containing Fig S1 was omitted from the original version of this Article. This has been corrected in the HTML version of the Article; the PDF version was correct at time of publication. https://doi.org/10.1038/s41598-020-58890-

A Glycoprotein in Shells of Conspecifics Induces Larval Settlement of the Pacific Oyster Crassostrea gigas

Settlement of larvae of Crassostrea gigas on shell chips (SC) prepared from shells of 11 different species of mollusks was investigated. Furthermore, the settlement inducing compound in the shell of C. gigas was extracted and subjected to various treatments to characterize the chemical cue. C. gigas larvae settled on SC of all species tested except on Patinopecten yessoensis and Atrina pinnata. In SC of species that induced C. gigas larvae to settle, settlement was proportionate to the amount of SC supplied to the larvae. When compared to C. gigas SC, all species except Crassostrea nippona showed lower settlement inducing activities, suggesting that the cue may be more abundant or in a more available form to the larvae in shells of conspecific and C. nippona than in other species. The settlement inducing activity of C. gigas SC remained intact after antibiotic treatment. Extraction of C. gigas SC with diethyl ether (Et2O-ex), ethanol (EtOH-ex), and water (Aq-ex) did not induce larval settlement of C. gigas larvae. However, extraction of C. gigas SC with 2N of hydrochloric acid (HCl-ex) induced larval settlement that was at the same level as the SC. The settlement inducing compound in the HCl-ex was stable at 100°C but was destroyed or degraded after pepsin, trypsin, PNGase F and trifluoromethanesulfonic acid treatments. This chemical cue eluted between the molecular mass range of 45 and 150 kDa after gel filtration and revealed a major band at 55 kDa on the SDS-PAGE gel after staining with Stains-all. Thus, a 55 kDa glycoprotein component in the organic matrix of C. gigas shells is hypothesized to be the chemical basis of larval settlement on conspecifics

SDS-PAGE gel image of <i>C. gigas</i> FD HCl-ex, F1 (fraction 1) and F2 (fraction 2) stained with Stains-all.

<p>SDS-PAGE was performed on 10% polyacrylamide gels; 10 µg protein content was loaded in each lane. M indicates the molecular weight markers. Molecular weights were estimated using the molecular weight marker “Broad Range” (BIORAD).</p

Percentages of post larvae on pepsin and trypsin treated FD HCl-ex of <i>C. gigas</i> SC.

<p>Shaded and open boxes represent pepsin and trypsin treated experiments, respectively. Data are means of 9 replicates and error bars represent standard deviations (SD). Lines connected groups that were compared using Wald test. Asterisks * indicate significantly different groups (p<0.05).</p

Percentages of post larvae on PNGase F and TFMS treated FD HCl-ex of <i>C. gigas</i> SC.

<p>Boxes with slanting lines indicate post larvae (%) settled on FD HCl-ex 100 mg SC eq subjected to the same treatment procedure but without trypsin. Data are means of 9 replicates and error bars represent standard deviations (SD). Lines connected groups that were compared using Wald test. Asterisks * indicate significantly different groups (p<0.05).</p

Experimental design for the characterization of the settlement inducer in <i>C. gigas</i> SC.

<p>Experimental design for the characterization of the settlement inducer in <i>C. gigas</i> SC.</p

Absorbance and eluted fractions of FD HCl-ex of <i>C. gigas</i> SC after filtration in Superdex 200 10/300 GL column, and the percentages of post larvae at 50, 100 and 200 mg SC equivalent of each of the pooled fractions (F1: 45–150 kDa, F2:1.3–44 kDa, and F3:<1.3 kDa molecular mass ranges).

<p>Vo indicates void volume. Data are means of 6 to 9 replicates and error bars represent standard deviations (SD). Letters indicate results of the post hoc Tukey HSD test. Values connected by the same letter are not significantly different (p≥0.05).</p

ANOVA result of the effect of species and amount of SC on <i>C. gigas</i> larval settlement.

<p> Statistics of the quasi-binomial GLM applied to the output for dependent variable larval settlement. Species refers to the 11 species of SC tested; amount refers to the weight of SC.</p

Percentages of post larvae that settled on SC of the different species of mollusks.

<p>Closed squares are means of 6 to 30 replicates and error bars represent standard deviation (SD). Letters indicate results of the post hoc Tukey HSD test of activities within species at 0, 10, 50 and 100 mg. Values connected by the same letter are not significantly different (p≥0.05).</p

Estimated percent settlement differences of the 10 molluscan species SC <i>vs. C. gigas</i> SC (0).

<p>Closed circles represent mean estimates and error bars are 95% confidence intervals. Estimated settlement differences between the ten molluscan species and <i>C. gigas</i> (as the reference) were calculated based on the odds ratios.</p